Machine Learning Engineer, Locus Robotics
Manufacturer of autonomous warehouse robots
Open for applications
Manufacturer of autonomous warehouse robots
201-500 employees
Open for applications
201-500 employees
Company mission
To transform commerce supply chains worldwide through the use of autonomous mobile robots.
Role
Who you are
- If you're excited about solving real-world optimization problems, building high-performance ML infrastructure, and working with autonomous agent simulations, this is your opportunity to make a significant impact
- Master’s degree or Ph.D. in Data Science, Computer Science, Mathematics, or a related field
- 4+ years of hands-on experience designing and deploying machine learning models in production, with a focus on reinforcement learning (RL) and multi-agent systems (MAS)
- Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code
- Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models
- Experience working with Polars and/or Pandas for high-performance data processing
- Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization and orchestration using Docker and Kubernetes
- Hands-on experience with reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3
- Practical knowledge of optimization algorithms and probabilistic modeling techniques (e.g., Bayesian methods, Gaussian Belief Propagation)
- Experience integrating models into real-time decision-making systems or multi-agent RL environments (MARL)
- Exposure to spatiotemporal data analysis, including time-series anomaly detection and forecasting
- Familiarity with ROS (Robot Operating System) for robotics or simulation integration
- Publications in top-tier conferences/journals (e.g., NeurIPS, ICML, ICRA, CVPR, ECCV, ICCV) are a plus
- Proficient English written and verbal communication skills required to collaborate effectively with internal and external teams
- Excellent analytical and problem-solving skills, with the ability to contribute effectively in a collaborative team environment
What the job involves
- At Locus Robotics, we’re developing advanced simulation tools and ML systems to optimize the behavior of large autonomous fleets in dynamic environments
- In this role, you will work on cutting-edge reinforcement learning (RL) models, multi-agent systems, and faster-than-real-time simulations to drive innovation in logistics, robotics, and beyond
- You’ll collaborate with a highly skilled team of engineers and data scientists to develop scalable ML models and deploy them into production environments using modern MLOps practices
- Utilize, develop, and enhance simulation tooling and infrastructure to enable faster-than-real-time modelling of 1,000+ autonomous agents for various use cases such as fleet optimization, logistics, or robotics
- Develop, deploy, and maintain machine learning models, with a strong focus on reinforcement learning (RL) and multi-agent systems to optimize fleet behavior in dynamic environments
- Implement and improve MLOps pipelines to support continuous training, deployment, monitoring, and scaling of machine learning models in production
- Collaborate with data engineers and software developers to ensure seamless integration of machine learning models with existing infrastructure and data pipelines
- Stay up to date with advancements in reinforcement learning, distributed computing, and ML frameworks to drive innovation in the organization
- Work with cloud-based solutions (AWS, GCP, or Azure) to deploy and manage machine learning workloads in a scalable manner
Salary benchmarks
Our take
Many order fulfilment warehouses rely on a combination of human workers and machinery to operate packaging assembly lines. However, these workflows are time-consuming and repetitive, showing the potential for human workers to be replaced with AI-driven robots.
Locus Robotics provides automated robotic technologies for fulfilment warehouses, offering a range of different robots for different workflows. Every robot outputs data that can be tracked and analyzed, and they can be installed rapidly and scaled depending on business size.
Whilst robots in warehouses is not a new concept, they are generally limited to warehouse giants such as Amazon. Locus Robotics, however, has taken a flexible and accessible approach to its technology, aiming to increase access and affordability so that smaller businesses can scale.
Having picked over three billion items across its network of customers, the company is well established. It has also seen significant funding which has supported international expansion. In the longer term, when market conditions allow, it will consider an initial public offering.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
25% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Nov 2022
$117m
SERIES F
Sep 2021
$50m
SERIES E
Total funding: $416m
Company HQ
Wilmington, MA
Leadership
Rick Faulk
(CEO)Experience as CEO and Chairman of Intronis & Barracuda Networks from 2013 to 2016. CEO of Quiet Logistics from 2016 to 2018.
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