7,542 Machine Learning Models jobs in the United States

Palo Alto, CA, Pittsburgh, PA, Detroit, MI, Remote

Latitude AI ( lat.ai ) develops automated driving technologies, including L3, for Ford vehicles at scale. Were driven by the opportunity to reimagine what its like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, youll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering all dedicated to making a real, positive impact on the driving experience for millions of people.

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Offboard Models team is a group of highly skilled and experienced professionals who specialize in cutting-edge computer vision and machine learning technology. Together, we collaborate to create auto-labeling and data augmentation solutions for autonomy consumers including perception and mapping.

On the auto-labeling front, the primary focus is on developing multi-view, multi-sensor deep learning models capable of leveraging the maximal sensing suite on our development and consumer vehicles to perform a wide range of tasks such as 3D object detection, lane line detection and scene segmentation.

What youll do:

• Develop auto-labeling and/or data augmentation solutions for addressing the data diversity and/or annotation needs for onboard perception
• Read literature, analyze raw data, and design state-of-the-art solutions
• Collaborate with perception experts and experienced roboticists on algorithm design, prototyping, testing, cloud deployment, and productization
• Develop clean and efficient software for auto-labeling and/or data augmentation modules interfacing with consumer modules such as perception and resimulation
• Build and maintain industry-leading software practices and principles
• Show initiative and be a valued team member in a fast-paced, innovative, and entrepreneurial environment

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong knowledge and experience (4+ years) in machine learning, with a proven track record of developing and deploying deep learning solutions using PyTorch, Tensorflow, or similar frameworks
• Experience in developing perception systems using sensors such as camera, LiDAR, and RADAR
• At least 4 years of development experience in Python/C++ environments

Nice to have:

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitudes team, mission and career opportunities at lat.ai !

The expected base salary range for this full-time position in California is $174,000 - $261,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitudes annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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Latitude AI develops automated driving technologies, including L3, for Ford vehicles at scale. We're driven by the opportunity to reimagine what it's like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you'll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering all dedicated to making a real, positive impact on the driving experience for millions of people.

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team: The Offboard Models team is a group of highly skilled and experienced professionals who specialize in cutting-edge computer vision and machine learning technology. Together, we collaborate to create auto-labeling and data augmentation solutions for autonomy consumers including perception and mapping.

On the auto-labeling front, the primary focus is on developing multi-view, multi-sensor deep learning models capable of leveraging the maximal sensing suite on our development and consumer vehicles to perform a wide range of tasks such as 3D object detection, lane line detection and scene segmentation.

What you'll do:

• Develop auto-labeling and/or data augmentation solutions for addressing the data diversity and/or annotation needs for onboard perception
• Read literature, analyze raw data, and design state-of-the-art solutions
• Collaborate with perception experts and experienced roboticists on algorithm design, prototyping, testing, cloud deployment, and productization
• Develop clean and efficient software for auto-labeling and/or data augmentation modules interfacing with consumer modules such as perception and resimulation
• Build and maintain industry-leading software practices and principles
• Show initiative and be a valued team member in a fast-paced, innovative, and entrepreneurial environment

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong knowledge and experience (4+ years) in machine learning, with a proven track record of developing and deploying deep learning solutions using PyTorch, Tensorflow, or similar frameworks
• Experience in developing perception systems using sensors such as camera, LiDAR, and RADAR
• Experience in developing object detection, lane detection, or semantic segmentation models
• At least 4 years of development experience in Python/C++ environments

Nice to have:

• Experience developing transformer models, diffusion models, or vision language models (VLM)

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

The expected base salary range for this full-time position in California is $174,000 - $261,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude's annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

• Model Development
  
  • Design and implement novel algorithms and architectures for large-scale foundation models (e.g. Diffusion models, Transformers, VAEs) using single-cell RNA-seq and other modalities.
  • Develop mechanistic interpretability methods to infer gene networks and regulatory mechanisms via attention, graph-based, and/or causal representation methods.
  • Build state-of-the-art perturbation models using multi-modal perturbation (small molecules, CRISPR, cytokines) and phenotypic data.
  • Pre-train, post-train and deploy generative AI models using proprietary datasets, and distributed training and inference on cloud platforms.
  • Establish clinically relevant benchmarking and evaluation frameworks to assess context generalization and guide model improvements.
  • Stay current with the latest research in foundation models, representation learning (across biology, NLP, vision, and audio), and perturbation modeling.
  Scientific Collaboration
  • Collaborate with interdisciplinary scientists from biology, chemistry, and technology teams to translate research questions into cutting-edge ML solutions.
  • Communicate technical concepts clearly to diverse scientific audiences.
  • Contribute to strategic roadmap planning and technical decisions.

• PhD in Computer Science, Computational Biology, or related field, OR Master's degree with 3+ years of relevant ML research or industry experience.
• Strong foundation in statistics, deep learning and generative AI.
• Proficient in Python and scalable ML frameworks (e.g. PyTorch, Hugging Face)
• Experience with high-dimensional biological data analysis (bulk/single-cell RNA-seq, Gene regulatory networks, PPI networks, multi-omics integration).
• Experience with chemical / CRISPR perturbation screen data (eg: Perturb-seq).
• Experience developing deep generative models for representation learning.
• Excellent communication skills and ability to work in interdisciplinary teams.

• Experience efficiently training and fine-tuning foundation models on omics data.
• Experience with cloud computing (AWS/GCP) and MLOps best practices.
• Experience with self-supervised learning, contrastive learning, domain adaptation and/or reinforcement learning.
• Knowledge of ML algorithms for network inference.
• Ability to work in a fast-paced, multidisciplinary, biotech environment.

• Push Boundaries: We create a legacy with breakthrough science in service of patients.
• Inject Energy: We build strengths from different perspectives and tell it like it is
• Own it: We transcend our job descriptions and relentlessly follow through on our commitments.
• Go all out: We work quickly and with conviction.

• Develop, fine-tune, and optimize foundation models for the robot, leveraging advanced techniques such as pre-training, fine-tuning, and retrieval-augmented generation (RAG).
• Translate high-level application goals into foundational AI solutions, delivering robust and scalable models that perform effectively in real-world scenarios.
• Build pipelines for training, evaluation, and deployment of models on various platforms, ensuring high performance and adaptability across diverse use cases.
• Stay at the forefront of research, incorporating cutting-edge advancements in AI and foundation models to enhance system capabilities and push technical boundaries.
• Own critical projects end-to-end, from model design and experimentation to deployment and continuous improvement.
• Collaborate with cross-functional teams, including data, software, and systems engineers, to integrate models seamlessly into production workflows.

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Deep understanding of machine learning concepts, including attention mechanisms, transformers, and training techniques.
• Experience working with fine-tuning, retrieval-augmented generation (RAG), prompt engineering, or reinforcement learning with human feedback (RLHF).
• Proficiency in programming languages and tools commonly used in machine learning (e.g. Python).
• A strong grasp of theoretical concepts and practical implementation of multimodal foundation models.

• Experience with deployment of models to edge devices for real-time inference.
• Experience with large-scale distributed training and optimization frameworks (e.g. PyTorch, TensorFlow) and familiarity with tools for model compression and quantization.
• General knowledge of robotics principles, including kinematics, dynamics, and control.
• Publications or contributions to the machine learning community, particularly in areas related to robotics or large language models.
• Excellent problem-solving skills, with the ability to innovate and experiment with novel approaches

• Model Development
  
  • Design and implement novel algorithms and architectures for large-scale foundation models (e.g. Diffusion models, Transformers, VAEs) using single-cell RNA-seq and other modalities.
  • Develop mechanistic interpretability methods to infer gene networks and regulatory mechanisms via attention, graph-based, and/or causal representation methods.
  • Build state-of-the-art perturbation models using multi-modal perturbation (small molecules, CRISPR, cytokines) and phenotypic data.
  • Pre-train, post-train and deploy generative AI models using proprietary datasets, and distributed training and inference on cloud platforms.
  • Establish clinically relevant benchmarking and evaluation frameworks to assess context generalization and guide model improvements.
  • Stay current with the latest research in foundation models, representation learning (across biology, NLP, vision, and audio), and perturbation modeling.
  Scientific Collaboration
  • Collaborate with interdisciplinary scientists from biology, chemistry, and technology teams to translate research questions into cutting-edge ML solutions.
  • Communicate technical concepts clearly to diverse scientific audiences.
  • Contribute to strategic roadmap planning and technical decisions.

• PhD in Computer Science, Computational Biology, or related field, OR Master's degree with 3+ years of relevant ML research or industry experience.
• Strong foundation in statistics, deep learning and generative AI.
• Proficient in Python and scalable ML frameworks (e.g. PyTorch, Hugging Face)
• Experience with high-dimensional biological data analysis (bulk/single-cell RNA-seq, Gene regulatory networks, PPI networks, multi-omics integration).
• Experience with chemical / CRISPR perturbation screen data (eg: Perturb-seq).
• Experience developing deep generative models for representation learning.
• Excellent communication skills and ability to work in interdisciplinary teams.

• Experience efficiently training and fine-tuning foundation models on omics data.
• Experience with cloud computing (AWS/GCP) and MLOps best practices.
• Experience with self-supervised learning, contrastive learning, domain adaptation and/or reinforcement learning.
• Knowledge of ML algorithms for network inference.
• Ability to work in a fast-paced, multidisciplinary, biotech environment.

• Push Boundaries: We create a legacy with breakthrough science in service of patients.
• Inject Energy: We build strengths from different perspectives and tell it like it is
• Own it: We transcend our job descriptions and relentlessly follow through on our commitments.
• Go all out: We work quickly and with conviction.

• Your primary responsibility will be to explore and develop new deep learning models to solve inverse problems in imaging.
• You'll also evaluate customer feedback and image data to gauge performance and refine your models based on real-world usage.

• PhD in related field, or equivalent industry experience
• Prior key contributor to significant deep learning projects for image enhancement or image processing
• Significant prior experience with CNNs and other common computer vision network architectures
• 2 years of hands-on experience with TensorFlow or PyTorch
• Good understanding of common image processing algorithms
• Working knowledge of C/C++
• Well-read on major recent research papers in deep learning for image or video enhancement

Headquartered in Silicon Valley, we are a newly established start-up, where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of Generative AI. Our team comprises leading minds and innovators in AI and Biological Science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine.

We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBM), we are pioneering a new era of biomedicine, with our LBM training leading to ground-breaking advancements and a transformative approach to healthcare. Our exceptionally strong R&D team and leadership in LLM and generative AI position us at the forefront of this revolutionary field. With headquarters in Silicon Valley, California, and a branch office in Paris, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.

Key Responsibilities:

• Design, develop, optimize, and maintain software systems for the entire foundation model development and deployment lifecycle (i.e., data pipeline, pre-training, fine-tuning, serving).
• Build and maintain scalable, efficient, and reusable codebases for large-scale foundation model training, adaptation, evaluation, and inference.
• Collaborate closely with data engineers and research scientists to integrate models into production environments.
• Implement and ensure best practices in software engineering, including code quality, testing, and documentation.
• Build and optimize robust back-end systems, APIs, and databases to support complex workflows.
• Ensure code quality, scalability, and performance through rigorous testing and code reviews.

• Bachelor's, Master's degree in Computer Science, Engineering, or related field. Experience in life sciences or healthcare is a plus.
• Strong programming skills in JavaScript, Python, and modern web development frameworks, and familiarity with GPU-accelerated tools (e.g., CUDA, cuDNN, Triton).
• Proficiency with major deep learning frameworks such as PyTorch, HuggingFace Transformers & Accelerate, or Megatron-LM/DeepSpeed.
• Familiarity with resource management and scheduling systems (e.g., SLURM, Kubernetes).
• Have direct ML Ops platform experience, such as kubeflow pipelines, argo workflows, apache airflow, or metaflow.
• Proficiency in back-end frameworks like Django, Flask, or Node. js, and database technologies (e.g., PostgreSQL, MongoDB).
• Expertise in distributed systems, cloud computing (AWS, GCP), and containerization tools (Docker, Kubernetes).

• Ph.D. degree in Computer Science, Engineering, or related field. Experience in life sciences or healthcare is a plus.
• Prior experience pre-training or serving large language models or large-scale foundation models.
• Experience with deep learning workflows.
• Knowledge of biological data types and challenges and experience with bioinformatics tools.
• Familiarity with version control systems like Git and CI/CD pipelines.
• Strong understanding of RESTful APIs, authentication, and deployment pipelines
• Familiarity with machine learning workflows and biological datasets.

The Carbon Robotics LaserWeeder™ leverages advanced robotics, computer vision, AI/deep learning, and lasers to eliminate weeds with sub-millimeter accuracy-all without herbicides. This innovative solution reduces environmental impact, promotes soil health, and helps farmers address labor shortages and rising costs. Designed in Seattle and built at our cutting-edge manufacturing facility in Richland, Washington, the LaserWeeder is setting a new standard for automated weed control. With $157 million in funding from prominent investors such as BOND, NVentures (NVIDIA's venture arm), Anthos Capital, Fuse Venture Capital, Ignition Partners, Revolution, Sozo Ventures, and Voyager Capital , Carbon Robotics is driving innovation.

As a no-nonsense team with a bias for action, we take pride in executing our ideas. Whether it's designing transformative technology or visiting farms to ensure our products are reliable and safe, we do whatever it takes to deliver for our customers.

Working here means tackling big problems with big impact. You'll find opportunities to grow professionally, solve complex challenges, and make meaningful contributions to a mission that matters. At Carbon Robotics, we trust our team to act independently and make practical, real-world decisions.

Join us as we innovate, execute, and build the future of farming together.

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As a Deep Learning Engineer at Carbon Robotics you will design experiments to test new models and algorithms, optimize them for daily deployments to operational resources in the field, document and produce reports on your findings, and integrate them with our robotics software stack.

• Build quickly through ownership and collaboration with Engineering and Product Management

• Professional experience designing and implementing novel deep learning architectures to deliver real world computer vision solutions
• Understanding of foundational mathematical principle of deep learning architecture
• Hands-on experience across the end-to-end Machine Learning workflow - including data preparation, pipeline development, experimentation, evaluation, and deployment
• Experience with developing deep learning models at scale from inception to business impact
• Familiarity with modern object detection techniques (vision transformers, embeddings, anchor-free)
• Comfortable navigating ambiguity and evolving technical landscapes
• Effective verbal and written communication skills to explain model details and behavior to non-technical staff and customers
• Experience in deep learning model optimization and deployment
• BS+ in Data Science, Computer Science, or related field

• Competitive salaries
• Pre-IPO Stock Options
• Generous Benefits:
  • Fully-paid medical, dental, and vision insurance premiums for you and all dependents
    • Choice of PPO or HDHP/HSA
    • Virtual Care - Doctor on Demand
    • Employee Assistance Program
  • Mental Health HRA
  • Restricted Healthcare Travel support
  • Menopause Support
  • Life Insurance
  • Long Term Disability
  • Flexible PTO
  • 401(k) plan
  • Pet Insurance
  • Commuter Benefits
• Work Culture: Be a part of an inclusive and tight-knit company culture that values innovation and mission-driven success.

We're Topaz Labs, an AI tech company that builds software to solve imaging problems like denoising, super-resolution, and deconvolution with deep learning. Over 1M photographers and designers trust us with their work, including on teams at Google, Nvidia, NASA, and more. We've processed over 1 billion images, achieved 1000% revenue growth in the last 4 years, and we're only getting started.

We're looking for a Deep Learning Researcher to help us push the state-of-the-art in image and video enhancement. Your primary responsibility will be to explore and develop new deep learning models to solve inverse problems in imaging. You'll also evaluate customer feedback and image data to gauge performance and refine your models based on real-world usage.

About us

• Rocketship growth and opportunity for impact ($3M - $30M revenue in four years)
• Over 1 million customers (including companies like Apple, NASA, Netflix) have used us for over 1 billion photos. Our tech has been covered by Fast Company, The Verge, Engadget, Mashable, BBC, and more
• World-class team that executes quickly, obsesses about the customer experience, and promotes from within
• Profitable company with infinite runway

• PhD in related field, or equivalent industry experience
• Prior key contributor to significant deep learning projects for image enhancement or image processing
• Significant prior experience with CNNs and other common computer vision network architectures
• 2 years of hands-on experience with TensorFlow or PyTorch
• Good understanding of common image processing algorithms
• Working knowledge of C/C++
• Well-read on major recent research papers in deep learning for image or video enhancement