Team Lead, Machine Learning Platform – Embark

Full time @Embark Career in Remote
  • California, United States, San Francisco, California, United States View on Map
  • Post Date : January 31, 2022
  • Apply Before : May 1, 2022
  • View(s) 40
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Job Detail

  • Job ID 41999
  • Career Level Mid-Senior
  • Gender All
  • Qualifications certificate
  • Language Requirement
  • Region North America
  • Other Classifications startup
  • Special Programs y-combinator
  • Remote Yes
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Job Description

Embark Trucks is America’s Longest-Running Self-Driving Truck Program and is bringing autonomous freight mainstream. As covered by the Wall Street Journal, CNBC, Forbes, TechCrunch and and other outlets, Embark went public via a ~$5 billion SPAC deal in November 2021, and is listed on Nasdaq under the symbol EMBK. Embark is headquartered in San Francisco, CA with operations centers in Fontana, CA and Houston, TX, moving freight daily using our purpose-built transfer hubs. Embark has aligned itself with truck manufacturers, shippers, and carriers to integrate our technology into the freight ecosystem, pursuing a business model where fleets own and operate Embark trucks. This is an incredibly exciting time for autonomous vehicles and our team is looking to grow.
Embark uses machine learning to solve some of the most challenging problems in self-driving. With engineers training new models every day, building and maintaining powerful infrastructure and data pipelines to enable fast iteration on our machine learning models is key to Embark’s success. The goal of ML Platform is to build performant and scalable infrastructure to accelerate the key inputs of the machine learning process, including ground truth data collection, data curation and exploration, training and evaluation.
Embark is hiring an experienced leader to grow the Machine Learning Platform team. The MLP lead will be expected to build a high-performing team to solve some of the hardest problems in machine learning ops. This is a highly technical role and we expect qualified candidates to bring significant technical experience in across data, infrastructure and machine learning.
 
Role Responsibilities:
 
Build a high-performing team to scale Embark’s machine learning efforts through a period of rapid growth as we solve some of the hardest problems in self-driving with machine learning.
Work closely with our perception and planning teams to execute on a roadmap that accelerates their efforts with a tight iteration cycle.
Foster a team culture that is collaborative, inclusive and with a passion for building excellent systems.
Be a hands-on technical contributor. As the leader of a small, focused team, you should feel comfortable being a technical contributor across our infrastructure and machine learning pipelines.
 
Team Responsibilities:
 
Build and maintain scalable data pipelines for collecting and storing ground truth and sensor data
Architect and implement databases and query engines that allow us to effectively curate the best data for training 
Build and maintain a hybrid machine learning platform enabling on-premises and cloud training and evaluation in the cloud, working directly with our ML teams to develop workflows that maximize their productivity.
Work with our perception and planning teams teams to build and scale efficient search systems for novel data across sensor perception and scenarios.
 
Expected Experience:
 
Demonstrated experience leading a high-performing team. You have previously managed a small team focused on data, infrastructure, or machine learning. You should be comfortable hiring, setting objectives, managing execution and growing a team.
BS or MS in computer science, engineering, or equivalent real-world experience.
Strong, demonstrated abilities working with Python.
Significant experience with cloud services such as AWS or GCP.
Expertise in backend services written in Python and using traditional relational databases like MySQL.
Experience curating and managing large datasets
A good working understanding of the machine learning process, including dataset collection and curation, training and evaluation pipelines
Bonus Experience:
 
Experience with open-source and/or commercial cloud ML platforms, such as Kubeflow, Metaflow, or Sagemaker.
Experience with training and deploying models built on common machine learning frameworks (Tensorflow, PyTorch, etc).
Experience collecting and working with ground truth data
Familiarity with containerization and orchestration frameworks (Docker, Kubernetes, etc).

 
 
At Embark we celebrate diversity and are committed to creating an inclusive environment for all employees.

At Embark we celebrate diversity and are committed to creating an inclusive environment for all employees.

Embark Trucks, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Embark in the Press:
The Wall Street Journal Embark Announces $5.2 Billion Deal to Go Public
Business Insider Embark’s Original Pitch Deck
Former €œMythbuster€ Jamie Hyneman Hitches a Ride in an Embark Self-Driving Truck
CNBC Our Partner Development Program
Forbes The Embark Universal Interface
Navigating Highway Work Zones with the Embark Driver

A few company highlights:
Embark Blog Series C and Transfer Hubs
Forbes 70 Million Dollar Series C 
Video Day in the life of a self-driving truck
Embark Blog Disengagement Report
30 Million Dollar Series B led by Sequoia
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