4,033 AI Algorithms jobs in the United States

Job Description

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.

• 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.

Join us as we embark on this journey to redefine the future of biology and medicine.

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

A global technology leader is seeking a Deep Learning Engineer with hands-on experience in AI, computer vision, and robotics automation. The ideal candidate will research and develop advanced perception algorithms for collaborative robots (COBOTs), enabling intelligent navigation, object detection, and obstacle avoidance within industrial settings.

This position is fully onsite in Mountain View, CA .

The Deep Learning Engineer will lead research and development in computer vision for autonomous manufacturing robots. This role combines innovation and application—designing, training, and deploying machine learning models that enhance robot perception and autonomy. You’ll work closely with robotics and automation engineers to bring advanced AI capabilities to life on the production floor.

Research and develop computer vision algorithms for COBOTs and autonomous robotic systems.

Design and implement deep learning models for object detection, obstacle avoidance, and scene understanding.

Collaborate with robotics engineers to integrate and deploy models into real-world manufacturing applications.

Optimize and evaluate perception systems for accuracy, efficiency, and real-time performance.

Conduct experiments, collect and analyze data, and refine models to improve system performance.

Apply Python and AI frameworks to build and validate end-to-end vision solutions.

Stay current on emerging technologies in deep learning, AI, and robotics.

Required Qualifications

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.

2–4 years of hands-on experience in Deep Learning and Computer Vision .

Proficiency in Python and frameworks such as TensorFlow or PyTorch.

Experience with Artificial Intelligence (AI) and Robotic Process Automation (Automation Anywhere) .

Proven ability to design, train, and deploy deep learning models for real-world applications.

Preferred Experience & Skills

Familiarity with robotic perception systems and sensor fusion.

Strong understanding of machine learning workflows and MLOps best practices.

Excellent collaboration and communication skills in cross-disciplinary teams.

Research mindset with a focus on experimentation and continuous improvement.

Job Description:

• 2-4 years of Deep Learning experience.

Role Description:

• Research in advance areas of Computer vision for COBOTS Autonomous Robots for Manufacturing Plant. The role involves designing perception systems, developing vision-based algorithms for navigation, object detection, obstacle avoidance and collaborate with robotics engineers to deploy models for real world applications

Essential Skills:

• Research in advance areas of Computer vision for COBOTS Autonomous Robots for Manufacturing Plant. The role involves designing perception systems, developing vision-based algorithms for navigation, object detection, obstacle avoidance and collaborate with robotics engineers to deploy models for real world applications

Skills required (MUST HAVE):

• Deep Learning
• Artificial Intelligence (AI)
• Robotic Process Automation - Automation Anywhere
• Python for Data Science

• Design, implement, and optimize deep learning models for complex tasks.
• Develop and maintain scalable machine learning pipelines for training, validation, and deployment.
• Collaborate with data scientists, software engineers, and product managers to define project requirements and deliver impactful AI features.
• Conduct thorough research and experimentation to evaluate new algorithms and techniques.
• Stay current with the latest advancements in AI and machine learning research.
• Optimize model performance for efficiency, accuracy, and latency.
• Write high-quality, well-documented code in Python and relevant ML frameworks (TensorFlow, PyTorch, etc.).
• Deploy machine learning models into production environments, ensuring reliability and scalability.
• Contribute to the architectural design of AI systems and platforms.
• Mentor junior engineers and share knowledge within the team.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of experience in machine learning, with a strong focus on deep learning.
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud platforms (AWS, GCP, Azure).
• Solid understanding of algorithms, data structures, and software engineering best practices.
• Experience with MLOps principles and tools for model deployment and monitoring.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork abilities.
• Proven track record of delivering successful ML projects.

• Lead research and development initiatives in advanced AI/ML and deep learning.
• Design, implement, and validate novel AI algorithms and models.
• Apply ML techniques to solve complex problems in areas such as NLP, computer vision, or recommender systems.
• Work with large-scale datasets, perform feature engineering, and optimize model performance.
• Collaborate with software engineers to integrate AI models into production systems.
• Mentor and guide junior AI scientists and engineers.
• Stay abreast of the latest research trends and advancements in the AI field.
• Publish research findings in top-tier conferences and journals.
• Present research results and project outcomes to technical and non-technical audiences.
• Contribute to the strategic direction of AI/ML research within the company.
• Develop and maintain robust ML pipelines and MLOps practices.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 8 years of hands-on experience in AI/ML research and development.
• Proven expertise in deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Strong programming skills in Python, with experience in relevant libraries (e.g., NumPy, SciPy, Pandas).
• Deep understanding of core ML algorithms, statistical modeling, and optimization techniques.
• Experience with large-scale data processing and distributed computing (e.g., Spark).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong publication record in leading AI conferences or journals.
• Ability to communicate complex technical concepts effectively.
• Experience in cloud platforms (AWS, Azure, GCP) for ML workloads is a plus.