Senior Machine Learning Engineer

Los Altos, CA

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Toyota Research Institute

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Research Software Engineering (RSE) is looking for a collaborative and versatile Senior Machine Learning (ML) Engineer to be an integral part of our fast-paced, agile development team. You will work closely with research teams, fellow software engineers, tech adoption staff, to stabilize, deploy and improve machine learning systems/models as needed to provide high-value innovative solutions that address the future-facing needs of internal Toyota customers.
The RSE and IE teams work closely together to provide software architecture and development services and know-how to TRI research teams while crafting, building, and operating cloud infrastructure and large-scale data solutions.
TRI envisions a future where Toyota products, enabled by TRI technology, spectacularly improve quality of life for individuals and society.
To achieve its Vision, TRI’s Mission is to build new tools and capabilities passionate about improving the human condition through research in energy & materials, robotics, machine learning, human-centered AI, and human interactive driving.
Discover, Nurture & Adopt (DNA) has the mission to enable innovation and transformation at Toyota by building a link between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared dedication.
Discover: Represents the “opportunity discovery” of research ideas that we learn from the Toyota ecosystem and address as challenge problems in our TRI-wide research portfolio and the “adoption discovery” opportunities of matches between our mature research results to technology transitions into the Toyota ecosystem.
Nurture: Provides supporting roles through the Research Software Engineering (RSE) and Information Engineering (IE) teams that help TRI’s research divisions grow and cultivate their research results through additional resources in software development, information management at the level each of the research divisions wants.
Adopt: Represents our efforts to transfer TRI’s mature research results to the Toyota ecosystem and the engineering behind the embodiment of minimum viable prototypes.T

Responsibilities

  • Be a key engineer on the design, development and operation of our Data and Machine Learning infrastructure.
  • Partner and work with other engineers and technical staff to understand ML infrastructure and data enrichment challenges while creating solutions that are timely, automatable, and scalable.
  • Understand and work to align with our roadmaps, especially the machine learning research engineering roadmap.
  • Analyze, understand and enthusiastically contribute to requirements from the research teamsPartner with team members to streamline, automate and scale solutions.
  • Make recommendations on architecture, whether to build or integrate existing tools.
  • Work with teams to build a backlog of epics and stories to implement machine learning capabilities.
  • Stay up-to-date with the latest industry standard tools and technologies in this technical area.
  • Design, implement and adapt solutions at a fast pace while writing observable automation using standard methodologies to minimize human operations.

Qualifications

  • 5+ years proven track record building software on cloud platforms (such as AWS) in python, go or a similar language.
  • 2+ years of experience enabling developers by building tools, APIs or frameworks.
  • Bachelor's Degree in Computer Science, Math, Physics or related field.
  • An understanding of how modern machine learning works, and the types of tools and infrastructure required to support ML operations and engineers.
  • Experience integrating automated systems with third-party APIs.
  • Experience with modern databases (cassandra, postgres, or similar) and data transformation (spark, kafka, or similar).
  • Experience with basic data analysis (pandas or similar).
  • Experience with developing production systems in linux and linux-hosted containerization.
  • Experience with continuous integration practices (separating production services) and observability.
  • Proficiency in Python and Unix is a minimum. Additional knowledge of C++ / CUDA is a plus, experience with AWS as well.
  • Good software engineering skills, grounded in principled standard methodologies.
  • Clear grasp on basic Linear Algebra, Optimization, Statistics, and Algorithms.
  • Deep experience with PyTorch, TensorFlow, Caffe, Keras, Theano or other deep learning frameworks is expected.
  • Capable multi-tasker able to optimally be responsible for your tasks in order to chip in on more than one project within a two-week sprint.
  • Excellent communication skills, capable of documenting your work as you go while remaining attentive and active on internal tools like Slack and Jira.
  • Build machine learning models using deep learning techniques for computer vision tasks such as semantic segmentation, object detection, video understanding, etc.
  • Address large scale challenges in the machine learning development cycle, especially around distributed training in the cloud and data engineering.
  • Manipulate high-volume, high-dimensionality, structured data from driving logs for training and testing deep networks.
  • Produce high quality tested code that enables large scale research and can be transferred to physical robots deployed in the real world.
  • Stay up to date on the state-of-the-art in Deep Learning ideas and software, in collaboration with our Research Scientists.
  • Work in a multidisciplinary team and collaborate with other teams across the company.
  • Present results in verbal and written communications, including potentially at top international conferences.
  • Deep Learning and Computer Vision expertise not required - but recommended.
  • You care about openness and delivering with integrity.
  • You value working in a setting and culture that places high value on diversity, equity and inclusion
The pay range for this position at commencement of employment is expected to be between $184,000 and $276,000/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.
Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
TRI provides Equal Employment Opportunity without regard to the applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.

Tags: Agile APIs Architecture AWS Caffe Cassandra Computer Science Computer Vision CUDA Data analysis Deep Learning Engineering Jira Kafka Keras Linear algebra Linux Machine Learning Mathematics ML infrastructure ML models Pandas Physics PostgreSQL Privacy Python PyTorch Research Robotics Spark Statistics TensorFlow Testing Theano

Perks/benefits: Career development Conferences Equity Medical leave Parental leave Salary bonus

Region: North America
Country: United States
Job stats:  12  3  0

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