What Jobs are available for Deep Learning in the United States?

Role Overview

An elite AI engineering team within a global organization is hiring a VP-level AI Engineer to lead the development and deployment of agentic AI solutions at enterprise scale. These systems will power internal automation and cost-efficiency efforts, touching millions of transactions and users across a complex, high-volume environment.

This role is about building and deploying production-grade LLM and agentic systems , not just experimentation or internal tools. You’ll be expected to design for scale, reliability, and real-world performance — with the full backing and reach of a global enterprise.

What You’ll Do

• Design and deploy LLM-based and agentic AI systems in cloud environments
• Lead architecture and development of production-ready AI applications
• Collaborate with engineering, infrastructure, and business partners to identify impactful AI opportunities
• Ship systems that reduce operational cost and increase automation across the organization
• Own solutions from prototype to deployment and long-term optimization

What We’re Looking For

Must-Haves

• 8+ years of experience in software engineering or AI/ML roles (commercial/industry)
• Hands-on experience deploying LLM-based systems at scale
• Strong skills in both ML model deployment and system architecture
• Prior ownership of AI products used by external users or across large orgs
• Experience in cloud-based environments (e.g., AWS, GCP, Azure)
• Track record of shipping AI into production , not just R&D or PoCs
• Stable career trajectory (ideally 2+ years per role)

Role Overview

An elite AI engineering team within a global organization is hiring a VP-level AI Engineer to lead the development and deployment of agentic AI solutions at enterprise scale. These systems will power internal automation and cost-efficiency efforts, touching millions of transactions and users across a complex, high-volume environment.

This role is about building and deploying production-grade LLM and agentic systems , not just experimentation or internal tools. You’ll be expected to design for scale, reliability, and real-world performance — with the full backing and reach of a global enterprise.

What You’ll Do

• Design and deploy LLM-based and agentic AI systems in cloud environments
• Lead architecture and development of production-ready AI applications
• Collaborate with engineering, infrastructure, and business partners to identify impactful AI opportunities
• Ship systems that reduce operational cost and increase automation across the organization
• Own solutions from prototype to deployment and long-term optimization

What We’re Looking For

Must-Haves

• 8+ years of experience in software engineering or AI/ML roles (commercial/industry)
• Hands-on experience deploying LLM-based systems at scale
• Strong skills in both ML model deployment and system architecture
• Prior ownership of AI products used by external users or across large orgs
• Experience in cloud-based environments (e.g., AWS, GCP, Azure)
• Track record of shipping AI into production , not just R&D or PoCs
• Stable career trajectory (ideally 2+ years per role)

NVIDIA is hiring software engineers at all experience levels to build and optimize the tools Deep Learning engineers use across the world to design, develop, and deploy AI applications. This position will embed you in an ambitious and diverse team that influences all areas of NVIDIA's AI platform and directly contributes to premiere Deep Learning frameworks - Tensorflow, PyTorch, and MXNet. In this role you will work with multiple teams at NVIDIA across fields, as well as collaborate with the open-source community to optimize the best AI platform in the world. What you will be doing: Optimize the performance of Deep Learning models for NVIDIA GPUs and systems. Study and tune Deep Learning training workloads at large scale. Optimize production AI models used by enterprise customers and partners. Build and support NVIDIA submissions to community benchmarks like MLPerf. Optimize the performance of influential, contemporary models coming out of academic and industry research, for NVIDIA GPUs and systems. Deliver the benefits of NVIDIA’s latest hardware and platform software innovations to the Deep Learning community. Inform design of new hardware generations, and core platform software components for NVIDIA GPUs and systems. What we need to see: BS or equivalent experience in Computer Science, Electrical Engineering or a related field. 2 years of experience with C++ and Python programming. Strong background with parallel programming, preferably on GPUs. Knowledge of Computer Architecture and/or Operating Systems. Proven experience developing large software projects. Excellent verbal and written communication skills. Ways to stand out from the crowd: Experience in PyTorch, Tensorflow or MXNet. Background with performance analysis and profiling of workloads. Participation in the open source community. Proven experience working with multidisciplinary teams. With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and dedicated people in the world working with us and our engineering teams are contributing to some of the hottest state of the art fields: Deep Learning, Artificial Intelligence, and Autonomous Vehicles. If you're a creative and motivated software engineer with a real passion for building fast software solutions, as well as impacting AI development worldwide, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 120,000 USD - 189,750 USD for Level 2, and 148,000 USD - 235,750 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 10, 2025. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. deeplearningaa415a4b-8b21-40fc-a65c-70d2b25ca29a

Job Description

Job Title: AI Research Engineer (Drug Discovery) 
Annual Base Salary: DOE, $110,000-$130,000 along with bonus eligibility and a comprehensive benefits package
Location: Los Angeles, CA

Our Mission
Formerly known as the Ellison Institute of Technology Los Angeles, the Ellison Medical Institute strives to spark innovation, leverage technology, and drive interdisciplinary, patient-centered research to continually enhance health, reimagine and redefine cancer care, and transform lives.
 
Established in 2016 as a medical research and development center, the Institute features innovation labs for artificial intelligence and molecular analytics and was among the first organizations to vertically integrate the interdisciplinary study and treatment of disease. We offer multifaceted programs, including a preventative medicine and cancer clinic, cross-disciplinary research laboratories, a health policy think-tank, and community outreach and educational programs.

Please visit emila.org for more details.

Job Summary
The Ellison Medical Institute is seeking a AI Research Engineer (Drug Discovery) to join the Applied AI program in support of the Institute’s data science and computational drug discovery initiatives.

This is an exceptional opportunity to contribute to high-impact, translational research in a collaborative environment that merges artificial intelligence, molecular science, and clinical medicine.

Why Join Us:

• Contribute to Transformative AI in Medicine: At the Ellison Medical Institute, your work will directly advance the application of artificial intelligence to therapeutic discovery, helping transform patient care and accelerate medical innovation.
• Collaborate Across Disciplines to Drive Innovation: You’ll work closely with scientists, clinicians, and computational experts in a dynamic, interdisciplinary setting that encourages creativity, rapid iteration, and meaningful impact from algorithm to clinic.
• Grow in a Supportive, Research-Driven Environment: You’ll receive mentorship from experienced AI and biomedical professionals, gaining exposure to the full lifecycle of AI model development, deployment, and validation within a real-world healthcare context. Whether your goals lie in academia, biotech, or applied AI research, your experience here will prepare you for success.

• AI Pipeline Development: Design, build, and maintain production-level, cloud-based AI systems that support drug discovery and molecular property prediction.
• Machine Learning Model Development: Develop and refine ML and deep learning models for computational chemistry, biomarker identification, and multi-modal data analysis.
• Cross-Functional Collaboration: Partner with data scientists, clinicians, and biomedical researchers to translate computational findings into actionable therapeutic insights.
• Documentation & Knowledge Sharing: Maintain thorough, reproducible records of methodologies, codebases, and results; contribute to internal documentation and shared resources.
• Communication & Reporting: Present results and model performance in internal meetings, technical reports, and research presentations for diverse stakeholders.
• Continuous Learning & Innovation: Stay at the forefront of advancements in AI, data science, and biomedical computing, integrating new methods and tools into the Institute’s research workflows.

• Required Education: Bachelor’s degree in Computer Science, Mathematics, Computational Biology or a related field.
• Required Experience:  At least 3 years of industry experience in dedicated AI and computational drug discovery roles or equivalent research positions.
• Required Skills & Experience:
  • Proficiency in Python, R, and SQL
  • Experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, and Pandas
  • Strong analytical and problem-solving skills
  • Excellent teamwork, documentation, and communication abilities
• Preferred Qualifications:
  • Experience analyzing multi-modal biomedical datasets
  • Strong background in statistics and computational modeling
  • Application development experience on Oracle Cloud Infrastructure or equivalent cloud platforms
  • Demonstrated ability to work collaboratively in an interdisciplinary research environment

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Job Description

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

At Field AI , we are moving beyond single-agent autonomy—scaling AI coordination across fleets of robots in unstructured, high-risk environments . Our work in Field Foundation Models™ (FFMs) is enabling multi-robot decision-making, strategic coordination, and decentralized intelligence at unprecedented levels. From large-scale robotic deployments in complex environments to real-time tactical decision-making, we are pioneering multi-agent AI that is explainable, risk-aware, and field-ready.

We are seeking a Multi-Robot Intelligence Research Engineer to design and implement scalable algorithms for coordination, decentralized control, and game-theoretic decision-making in multi-robot systems. This role is at the intersection of robotics, AI, and mathematical game theory , pushing the boundaries of large-scale, real-world autonomy .

• Develop fundamental algorithms for multi-agent coordination (including differentiable game theory, mean-field control, and decentralized optimization ) to enable fleets of autonomous robots to operate in real-world, high-stakes environments.
• Design computationally tractable formulations of multi-agent Nash equilibria, Stackelberg games, and cooperative decision-making strategies , ensuring robust and scalable decision-making across heterogeneous robotic teams.
• Build predictive models for multi-agent interaction dynamics , leveraging graph-based learning and control-theoretic formulations to drive efficient coordination in dynamic, adversarial, and uncertain settings.
• Develop distributed inference and control policies using neural PDEs, mean-field game-theoretic methods, and scalable stochastic optimization for real-time at-scale robotic interaction.
• Bridge theory with deployment —integrate multi-agent planning, auction-based task allocation, and decentralized multiagent reinforcement learning (MARL) into hardware-in-the-loop robotic systems operating at scale .
• Push the limits of explainability in multi-agent AI , ensuring tractability, convergence guarantees, and real-world feasibility while maintaining risk-aware and uncertainty-resolving decision-making .
• Collaborate across teams to transition multi-agent models from high-fidelity simulations to real-world deployments , working alongside robotics engineers, AI/ML researchers, and field roboticists to ensure seamless real-world operation.

• Ph.D. in Applied Mathematics, Game Theory, Control Theory, Computer Science, or a related field , with expertise in multi-agent decision-making and coordination algorithms .
• Deep understanding of game-theoretic methods —including differential games, Nash equilibria, mean-field games, and Stackelberg equilibria —with a focus on scalability and tractability .
• Experience with multi-agent RL (MARL) and distributed optimization for large-scale robotic coordination in imperfect information settings.
• Hands-on experience implementing multi-agent algorithms in real-time robotic or AI-driven systems , with exposure to hardware constraints, real-world latency, and stochastic disturbances .
• Proficiency in Python, C++, or Julia , with experience in optimization libraries (e.g., CVXPY, Gurobi, JAX), reinforcement learning frameworks (e.g., RLlib, Acme), and multi-robot simulators .
• Experience working with large-scale robotic coordination (e.g., drone swarms, autonomous fleets, or industrial automation systems) is a strong plus.
• Ability to transition theoretical insights into scalable, field-deployable systems , ensuring robustness under uncertainty and adaptability to real-world constraints.

Compensation and Benefits

Our salary range is between ($70,000 - $300,000 annual), but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience.  Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

Why Join Field AI?

We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.

Be Part of the Next Robotics Revolution

To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.

We are headquartered in always-sunny Mission Viejo (Irvine adjacent), Southern California and have US based and global teammates. 

Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!

We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.

Job Description

Who We Are:

Bandwidth , a prior "Best of EC" award winner, is a global software company that helps enterprises deliver exceptional experiences through voice, messaging, and emergency services. Reaching 65+ countries and over 90 percent of the global economy, we're the only provider offering an owned communications cloud that delivers advanced automation, AI integrations, global reach, and premium human support. Bandwidth is trusted for mission-critical communications by the Global 2000, hyperscalers, and SaaS builders!

At Bandwidth, your music matters when you are part of the BAND. We celebrate differences and encourage BANDmates to be their authentic selves. #jointheband

What We Are Looking For:

Bandwidth's Research & Development (R&D) team is at the forefront of exploring and harnessing transformative technologies to define the next generation of communication experiences. We operate as a small, agile, and T-shaped group, diving deep into emerging areas like Artificial Intelligence and Machine Learning. We're seeking a highly motivated AI/ML Engineer to join this dynamic team in our Raleigh, NC headquarters.

You thrive in a collaborative, fast-paced environment where you can rapidly iterate on ideas and prototypes. You have a startup mentality, comfortable with ambiguity and driven by a relentless curiosity to explore, build, and learn. If you're passionate about applying cutting-edge AI/ML, especially Large Language Models (LLMs), to solve real-world problems and shape future products, this is the role for you. This position requires working full-time from our Raleigh office.

What You'll Do:

• Dive deep into the latest AI/ML research, particularly in the LLM space, identifying opportunities relevant to Bandwidth's domain.
• Design, build, and test proof-of-concepts and prototypes for novel AI-powered features and services.
• Implement and integrate AI/ML models, including those based on LLMs, into potential future Bandwidth offerings.
• Collaborate intensely within a small, cross-functional R&D team, sharing knowledge and contributing to a T-shaped skill set.
• Experiment with various AI techniques, including advanced prompting strategies, Retrieval-Augmented Generation (RAG), and potentially agentic systems.
• Stay constantly updated on the rapidly evolving AI landscape, evaluating new tools, models, and methodologies.
• Leverage LLM-powered IDEs and development tools (like GitHub Copilot, Cursor, etc.) to accelerate the innovation cycle.
• Clearly articulate and present research findings, experiment results, and prototype demonstrations to technical and non-technical stakeholders.

What You Need:

• Bachelor's degree in Computer Science, AI, ML, or a related technical field, or equivalent practical experience.
• Demonstrable expertise and hands-on experience in Artificial Intelligence and Machine Learning, with deep knowledge in at least one specific AI domain (e.g., NLP, LLMs, Speech Recognition).
• Proven experience (typically 3+ years) designing, building, and evaluating AI/ML models and systems.
• Strong programming skills, particularly in Python and familiarity with common ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face).
• Solid understanding and practical experience with Large Language Models (LLMs) and associated concepts, including Retrieval-Augmented Generation (RAG) and various prompting techniques (e.g., Zero-shot, Few-shot, Chain of Thought).
• Experience implementing services or applications built on top of foundational LLMs (via APIs or open-source models).
• Proven ability to thrive in a small, highly collaborative team environment with an urgent, results-oriented culture. Significant experience in startups or similar fast-moving, resource-constrained organizations is highly desirable.
• A relentless curiosity and passion for exploring new technologies and techniques in the AI/ML space.
• Experience using LLM-powered IDEs or coding assistants.
• Excellent problem-solving skills and the ability to navigate ambiguity.
• Must be able to work full-time from the Bandwidth headquarters in Raleigh, NC.

Bonus Points:

• Master's degree or PhD in Computer Science, AI, ML, or a related field.
• Experience with LLM training, fine-tuning (e.g., LoRa), and/or developing custom evaluation benchmarks.
• Familiarity with advanced AI architectures and concepts such as agentic systems (e.g., ReAct), multi-modal models, Mixture of Experts (MoE), or LLM tooling/external capabilities.
• Experience with MLOps practices and cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform).
• Familiarity with AI Developer and Agentic Frameworks (e.g., OpenAI, LangChain, CrewAI, Autogen)
• Experience contributing to AI/ML research, publications, or open-source projects.

The Whole Person Promise:

At Bandwidth, we're pretty proud of our corporate culture, which is rooted in our "Whole Person Promise." We promise all employees that they can have meaningful work AND a full life, and we provide a work environment geared toward enriching your body, mind, and spirit. How do we do that? Well…

• 100% company-paid Medical, Vision, & Dental coverage for you and your family with low deductibles and low out-of-pocket expenses.
• All new hires receive four weeks of PTO.
• PTO Embargo. When you take time off (of any kind!) you're embargoed from working. Bandmates and managers are not allowed to interrupt your PTO – not even with email.
• Additional PTO can be earned throughout the year through volunteer hours and Bandwidth challenges.
• "Mahalo moments" program grants additional time off for life's most important moments like graduations, buying a first home, getting married, wedding anniversaries (every five years), and the birth of a grandchild.
• 90-Minute Workout Lunches and unlimited meetings with our very own nutritionist.

Are you excited about the position and its responsibilities, but not sure if you're 100% qualified? Do you feel you can work to help us crush the mission? If you answered 'yes' to both of these questions, we encourage you to apply! You won't want to miss the opportunity to be a part of the BAND.

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Job Description

SEON is the command center for fraud prevention and AML compliance, helping thousands of companies worldwide stop fraud, reduce risk and protect revenue. Powered by 900+ real-time, first-party data signals, SEON enriches customer profiles, flags suspicious behavior and streamlines compliance workflows - all from one place. SEON provides richer data, more flexible and transparent analysis, and faster time to value than any other provider on the market. We’ve helped companies reduce fraud by 95% and achieve 32x ROI, and we’re growing fast, thanks to our partnerships with some of the world’s most ambitious digital brands like Revolut, Wise, and Bilt.

We are currently looking for a rare combination of research brilliance and pragmatic engineering, someone who can transform cutting-edge computer vision and NLP research into high-assurance AI systems for regulatory compliance and identity verification.

As the founding member of SEON's AI Innovation team, you'll drive a research agenda that reimagines how document authentication, identity verification, and AML screening work in production environments. Your solutions will need to meet the exacting standards of financial regulators while delivering tangible advantages in accuracy, explainability, and cost-effectiveness over legacy systems.

This is an opportunity to build something from first principles. You'll work directly with C-level executives to shape our AI strategy, develop production-ready prototypes, and establish our technical approach to high-stakes decision systems in a regulated environment. Success means creating solutions that can be validated with mathematical rigor, deployed into production environments, and serve as the foundation for SEON's next generation of AI-powered fraud prevention products.

This is a Hybrid role and will be based out of our Austin office.

WHAT YOU’LL DO:

• Design and implement advanced architectures for document understanding that can extract, normalize, and verify complex identity data from diverse document types

• Create novel solutions for AML name screening that incorporate context-aware matching, transliteration handling, and explainable decision frameworks

• Develop evaluation methodologies that rigorously benchmark new approaches against both academic standards and real-world performance metrics

• Design sophisticated AI interaction architectures that optimize model performance across document analysis and fraud prevention systems

• Build systematic frameworks for collecting and analyzing model performance data to guide continuous improvement cycles

• Architect end-to-end systems for document analysis that combine computer vision, OCR, and structured information extraction with robust verification logic

• Build high-assurance systems with appropriate guardrails, confidence scoring, and formal verification methods

• Develop APIs and integration patterns that allow seamless incorporation of AI capabilities into SEON's broader platform

• Create comprehensive evaluation suites for measuring model accuracy, fairness, and reliability against established benchmarks

• Establish methodologies for training, fine-tuning, and continuously improving AI models with domain-specific data

• Evaluate emerging research, tools, and platforms from major cloud providers and research institutions

• Develop product-focused neural reasoning frameworks that balance performance with explainability requirements

• Create innovative evaluation methodologies that validate AI systems against both technical and business metrics

• Partner with product management to translate research innovations into market-ready capabilities

• Collaborate with compliance and legal teams to ensure AI systems meet regulatory requirements for explainability and audibility

• Build relationships with academic researchers and industry partners to accelerate innovation

• Mentor and guide engineers as the Austin AI Innovation team grows

WHAT YOU’ll BRING:

• Deep expertise in computer vision, particularly document understanding, OCR, and information extraction

• Strong understanding of modern NLP techniques, especially those applicable to entity recognition, name matching, and contextual understanding

• Experience designing and implementing high-assurance AI systems with appropriate verification, validation, and explainability

• Demonstrated ability to translate research into working prototypes and production systems

• Expertise in LLM behavior engineering for large language models and multimodal AI systems

• Demonstrated ability to design and implement effective evaluation frameworks for AI models

• Experience with systematically improving AI model performance through iterative testing and refinement

• Applied Research experience in Computer Science, Electrical Engineering, or related field

• Publication record in relevant research areas is a plus

• Entrepreneurial mindset with the ability to operate independently and build from first principles

• Excellent communication skills with ability to explain complex technical concepts to both technical and non-technical audiences

AMAZING IF YOU ALSO HAVE:

• Experience working on regulated applications of AI, particularly in fintech, identity verification, or compliance

• Knowledge of formal verification techniques for AI and machine learning systems

• Familiarity with challenges specific to identity documents, including cross-lingual processing, security feature verification, and fraud detection

• Track record of building applications that balance performance with interpretability requirements

• Experience with hybrid architectures that combine knowledge bases with learned capabilities

• Product management experience with AI-powered solutions in enterprise environments

SEON Technologies collects and processes personal data in accordance with applicable data protection laws. If you are a European Job Applicant see the privacy notice for further details.

SEON is an equal opportunity employer. We strive to embrace what makes each one of us unique; we each have our own story. Whether looking at our current staff or future team members, we believe that everyone has something to contribute, and our employment practices reflect that. We do not make an employment decision based upon race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Please let your recruiter know if you need reasonable adjustments to our recruitment process.

Job Description

Founded in 2016 in Silicon Valley, Pony.ai has quickly become a global leader in autonomous mobility and is a pioneer in extending autonomous mobility technologies and services at a rapidly expanding footprint of sites around the world. Operating Robotaxi, Robotruck and Personally Owned Vehicles (POV) business units, Pony.ai is an industry leader in the commercialization of autonomous driving and is committed to developing the safest autonomous driving capabilities on a global scale. Pony.ai’s leading position has been recognized, with CNBC ranking Pony.ai #10 on its CNBC Disruptor list of the 50 most innovative and disruptive tech companies of 2022. In June 2023, Pony.ai was recognized on the XPRIZE and Bessemer Venture Partners inaugural “XB100” 2023 list of the world’s top 100 private deep tech companies, ranking #12 globally. As of August 2023, Pony.ai has accumulated nearly 21 million miles of autonomous driving globally. Pony.ai went public at NASDAQ in Nov. 2024.

• Work with experts in the field of self-driving vehicles on designing and developing large-scale foundation models trained on vast amounts of real world data.
• Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, reinforcement learning, imitation learning, etc) to these problems; scale them to data pipelines; and streamline them to run in real-time on the cars.
• Develop and deploy deep learning models, including vision language models (VLMs) and Large Language Models (LLMs)
• Design and implement multi-modality and multi-task models focusing on 3D object detection and tracking, segmentation, semantics understanding, video understanding, scene understanding, traffic control, or trajectory prediction, etc.
• Optimize deep learning models to run robustly under tight run-time constraints.

Requirements

• Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field
• Strong background in deep learning, with experience in model design, training and evaluation.
• Experience with deep learning research and tools.
• Proficiency in software design and development using Python and C++.
• Experience working with large-scale datasets, data preprocessing, and pipeline management.

Preferred Experience

• Publications on top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/ICLR/AAAI
• Experience in applying ML/DL for behavior prediction, imitation learning, motion planning.
• Experience in deploying deep learning algorithms for real time applications, with limited computing resources.
• Experience in convex optimization, computational geometry or linear algebra.
• Experience in GPU/CUDA/TensorRT
• Previous internships involving large-scale deep learning models and systems
• Preferred graduate before Dec 2026

Note

This position is fully onsite in Fremont, at least 3 months.

Compensation

• Master: $7000/month
• PhD: $10,000/month

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