Senior/Staff Machine Learning Engineer, Dexterity

$170-225k

AWS
Docker
Kubernetes
GCP
Python
Tensorflow
C++
Azure
Flask
PyTorch
Git
Senior and Expert level
San Francisco Bay Area

Office located in Redwood City, CA

Dexterity

Robotics for logistics, warehouses, and supply chain

Open for applications

Dexterity

Robotics for logistics, warehouses, and supply chain

201-500 employees

B2BArtificial IntelligenceEnterpriseLogisticsManufacturingRoboticsSupply ChainSaaS

Open for applications

$170-225k

AWS
Docker
Kubernetes
GCP
Python
Tensorflow
C++
Azure
Flask
PyTorch
Git
Senior and Expert level
San Francisco Bay Area

Office located in Redwood City, CA

201-500 employees

B2BArtificial IntelligenceEnterpriseLogisticsManufacturingRoboticsSupply ChainSaaS

Company mission

Dexterity's mission is to help people thrive and grow by freeing them to do work that humans do best, by transforming the world to make work more purposeful.

Role

Who you are

  • Experience with RGBD datasets and point clouds is very important to the type of problems you will encounter in this role and experience in the areas of ML and CV for autonomous vehicles or robotics is very useful
  • In addition, a solid grounding in writing optimized code in c++ and python as well as understanding the limitations of languages and frameworks is critical
  • Additionally, familiarity with cloud infrastructure to build training and serving pipelines is also a key aspect to this role
  • At Dexterity, our use cases require low latency inference that approaches real time and therefore you must be able to build highly performant models and serving architectures
  • While an understanding of open source solutions is a useful prerequisite, we also require that the candidate has experience building their own models and setting up training pipelines
  • BS/MS/Ph.D. in Computer Science, Machine Learning or a related discipline, or equivalent experience
  • 5 or more years of related work experience
  • Prior experience building, training and deploying production ML models from scratch using PyTorch and Tensorflow
  • Strong knowledge of Modern C++ and Python
  • Experience using profilers and debuggers to optimize code
  • Experience building and maintaining production code
  • Experience with serving architectures like NVIDIA Triton, TorchServe and Tensorflow Serving, flask and others
  • Strong academic background and knowledge of ML and academic papers
  • Experience with cloud infrastructure such as AWS, GCP, Azure etc. and experience using this infrastructure to create training and serving pipelines
  • Ability to trace and solve problems across interconnected systems, pipelines and applications
  • Experience deploying software and configuring distributed systems
  • Experience with Git and modern CI pipelines

Desirable

  • Experience with Docker and Kubernetes
  • Previous startup experience

What the job involves

  • In this role at Dexterity, you will be working on building Machine Learning models for computer vision
  • The role will involve understanding our current systems and their limitations and bringing your expertise in augmenting and developing ML models
  • Additionally, you will be responsible for updating and scaling our current ML pipelines to cover more scenarios and improve accuracy
  • You will leverage your expertise around the subfields of semantic segmentation and instance segmentation, keep up to date with the latest developments in these areas and implement them using platforms like Pytorch, Tensorflow etc.
  • Your job will not only be finding and perfecting the right model(s) and architecture, but also identifying key problems throughout our system that can be solved with machine learning
  • The end to end process of gathering, augmenting, labeling data and curating datasets, studying performance and optimizing quality of the model, as well as training, deploying and troubleshooting models on the field will be under your purview

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Insights

Top investors

1% employee growth in 12 months

Company

Company benefits

  • Flexible and generous vacation and holidays
  • Comprehensive healthcare benefits for you and your family
  • Retirement plan (subject to country of employment)
  • Wellbeing and fitness offerings
  • Insurance programs
  • Discounts and perks
  • Meals and snacks at our sites

Funding (last 2 of 3 rounds)

Mar 2025

$95m

LATE VC

Oct 2021

$140m

SERIES B

Total funding: $291.2m

Our take

Dexterity emerged from stealth at an opportune, albeit tough, time in 2020, just as an accelerating labour crunch drove major demand for automated solutions in factories and warehouses. The company managed a major fundraise and immediately moved on to bigger and better things: expanding into the Japanese market, partnering with supply chain automation leader Dematic and achieving unicorn status with a greater than $1 billion valuation.

Unlike other companies which are fixated on developing increasingly sophisticated, more human-like robots, Dexterity’s takes a comparatively simple hardware approach. Its machines take care of highly repetitive tasks, while its SaaS platform shares everything it learns with each robot, amplifying intelligence across the fleet. Rather than seeking to replace human workforces it aims to augment them, freeing skilled workers for more complex tasks.

Considering that the worldwide labour shortage is heavily impacting the industrial sector, Dexterity is in a promising position to continue its upward trajectory over the next few years.. Indeed its recent partnerships with Sumitomo to supply 1,500 Dexterity robots in their warehouses and with FedEx for autonomous trailer loading are encouraging signs of things to come for the company.

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Freddie

Company Specialist at Welcome to the Jungle