Woven Planet

Engineering Manager, ML Platform – Behavior

Woven Planet

full-time

Posted on:

Location Type: Hybrid

Location: Palo Alto • California • 🇺🇸 United States

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Salary

💰 $161,000 - $264,500 per year

Job Level

Mid-LevelSenior

Tech Stack

CloudPythonPyTorchTensorflow

About the role

  • Define the team’s short‑term and long‑term technical direction while collaborating on broader cross‑functional strategic initiatives.
  • Initiate and influence cross‑functional teams toward common development goals to drive innovation
  • Enable and support your team to be more effective through coaching, leading by example, providing high‑quality code and design‑document reviews, and delivering rigorous reports.
  • Collaborate with team members to design, develop, deploy, and evaluate state‑of‑the‑art pipelines and processes for ML model development, testing, and deployment.
  • Lead the execution of projects by defining efficient engineering processes, mitigating technical risks, and advocating for architectural improvements that enhance system reliability and scalability.
  • Increase speed of the component- and system-level model iteration while maintaining cost efficiency.
  • Drive organizational metrics towards performance, safety, and quality.
  • Design reusable software components as part of an integrated system.
  • Understand and champion software practices that produce maintainable code, including continuous integration, code review, etc.
  • Work in a globally distributed department (US, Japan, London)
  • Work in a hybrid workspace, with the requirement to be present in our Palo Alto office three days a week.

Requirements

  • BSc / BEng (MS / PhD nice-to-have) in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience.
  • 3+ years of experience managing engineering teams, with a focus on technical leadership, team development, and delivering high-impact projects in the automotive industry.
  • Experience with Python, PyTorch/Tensorflow, and software engineering best practices.
  • Experience in the full MLOps cycle covering data cleansing, data sampling, data curation, pre-processing, training, testing, evaluation, deployment, inference optimization and deployment in the cloud and on edge compute platforms.
  • Deep understanding of runtime complexity, space complexity, distributed computing, and the application of these concepts in concrete, distributed ML training and evaluation.
  • Experience working with temporal data and/or sequential modeling.
  • Strong communication skills with the ability to communicate concepts clearly and precisely.
  • Ability to write code in C++ and python.
  • Ability to lead within a globally distributed department
  • Excellent communication, skilled collaboration, and principled interactions.
  • Passionate about self-driving car technology and its potential for humanity.
Benefits
  • Excellent health, wellness, dental and vision coverage
  • A rewarding 401k program
  • Flexible vacation policy
  • Family planning and care benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
PythonPyTorchTensorFlowMLOpsdata cleansingdata samplingdata curationpre-processingtrainingC++
Soft skills
technical leadershipteam developmentcommunicationcollaborationcoachingproblem-solvinginfluencingreportinginnovationprincipled interactions
Certifications
BScBEngMSPhD