Karkidi
Machine Learning Engineer
Karkidi, Berkeley, California, United States, 94709
The Opportunity
We’re looking for a driven machine learning engineer comfortable working on large integrated machine learning systems. Experience with robots or other embodied systems (such as autonomous vehicles) is a bonus.
If our mission of revolutionizing robotics through machine learning resonates with you, get in touch and let’s talk about how we can create the next generation of AI-powered capable robots together.
Responsibilities
Collaborate with internal research scientists and our partner labs at top academic research universities, including MIT, Stanford, Berkeley, CMU, Columbia, and Princeton to drive pioneering research at scale. Build, improve, and robustify end-to-end integrated ML pipelines for training multimodal (language, images, video, actions) models at scale. Train, finetune, and serve robot foundation models with a strong MLOps mindset. Build processes for integrating collaboration-produced and open-source advancements and code into our internal stack. Build and improve large data pipelines for foundation model training. Be a key member of the team and play a critical role in rapid progress measured by both the development of internal capabilities and high-impact external publications. Qualifications
2+ years of professional ML engineering experience at an AI/ML-focused organization. Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision. Experience training large-scale foundation models (VLMs, text-to-video models, etc) utilizing distributed training and high-performance optimization techniques such as quantization, mixed precision, model parallelism, data parallelism or FSDP. Extensive practical experience with PyTorch. Strong proficiency in Python and software development best practices such as unit testing, documentation, code review, continuous integration, and dependency management. Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management. An ability to move fast and switch between modes of rapid prototyping and robust implementation as required. Nice to haves
Experience deploying models on embodied systems/robots. Experience working in mixed teams of research scientists and engineers. Experience Amazon EC2, S3, and/or Sagemaker. Experience with Bazel. The pay range for this position at commencement of employment is expected to be between $165,760 and $238,280/year for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave) and an annual cash bonus structure. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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Collaborate with internal research scientists and our partner labs at top academic research universities, including MIT, Stanford, Berkeley, CMU, Columbia, and Princeton to drive pioneering research at scale. Build, improve, and robustify end-to-end integrated ML pipelines for training multimodal (language, images, video, actions) models at scale. Train, finetune, and serve robot foundation models with a strong MLOps mindset. Build processes for integrating collaboration-produced and open-source advancements and code into our internal stack. Build and improve large data pipelines for foundation model training. Be a key member of the team and play a critical role in rapid progress measured by both the development of internal capabilities and high-impact external publications. Qualifications
2+ years of professional ML engineering experience at an AI/ML-focused organization. Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision. Experience training large-scale foundation models (VLMs, text-to-video models, etc) utilizing distributed training and high-performance optimization techniques such as quantization, mixed precision, model parallelism, data parallelism or FSDP. Extensive practical experience with PyTorch. Strong proficiency in Python and software development best practices such as unit testing, documentation, code review, continuous integration, and dependency management. Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management. An ability to move fast and switch between modes of rapid prototyping and robust implementation as required. Nice to haves
Experience deploying models on embodied systems/robots. Experience working in mixed teams of research scientists and engineers. Experience Amazon EC2, S3, and/or Sagemaker. Experience with Bazel. The pay range for this position at commencement of employment is expected to be between $165,760 and $238,280/year for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave) and an annual cash bonus structure. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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