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Senior/Staff Machine Learning Engineer

Mountain View, CA

Who we are

Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world’s first fully driverless commercial transportation service with Walmart. Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation. 

The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations. 

About the role

We are seeking a high-impact, technically deep Machine Learning Engineer to help develop and deploy cutting-edge ML solutions for our autonomous vehicle (AV) stack. This role is ideal for engineers who are excited about building models end-to-end - from data pipelines to model training, and finally to real-time deployment in highly optimized systems.

You will work closely with cross-functional teams including perception, planning, infrastructure, and systems engineering to ensure models are efficient, scalable, and production-ready for both on-vehicle deployment and cloud-based workflows.

 
This role is onsite 5 days a week at our Mountain View, CA office!

What you'll do

  • End-to-End Model Development. Drive the full lifecycle of ML model development: from data strategy and preprocessing, through training, evaluation, optimization, and deployment in production systems (on-vehicle and cloud).
  • Efficient Neural Network Design. Develop compact and efficient neural networks using techniques like quantization, pruning, sparsification, and model compression to meet strict latency and power constraints for AV hardware.
  • Foundation Model Building. Build core models that power key autonomous driving functions - including perception, prediction, and planning - for both real-time vehicle systems and offline processing.
  • Simulation and Scenario Generation. Create generative models to simulate rare or complex driving scenarios, enabling large-scale virtual validation of ML components.
  • Scalable Cloud Infrastructure. Design high-throughput, horizontally scalable pipelines for training, evaluation, and large-scale inference in cloud environments.
  • Data Workflow Engineering. Streamline the data lifecycle by designing automated, reliable pipelines for dataset curation, annotation, preprocessing, and continuous feedback from field data.
  • Tooling and Visualization. Develop tools for visualization, diagnostics, and performance monitoring to rapidly iterate and improve ML model behavior.

What we're looking for

  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Optimization, or a related field.
  • 4+ years of experience in developing and deploying large-scale ML systems, preferably in the autonomous driving domain or real-time applications.
  • Strong Python skills for model development and prototyping (e.g., PyTorch, TensorFlow).
  • Proficient in C++ for integrating models into high-performance real-time systems.
  • CUDA experience is a plus for low-level optimization.
  • Deep understanding of ML workflows: data curation, preprocessing, model training, ablation studies, evaluation, deployment, and inference optimization.
  • Experience optimizing models for inference performance on real-time or embedded systems.
  • Experience with software architecture, latency optimization, system-level debugging, and data flow analysis.
  • Experience with cloud-based ML training pipelines, preferably using platforms like Azure.
  • Publications in areas related to efficient machine learning, such as model acceleration techniques.
  • Prior contributions to large-scale ML systems in production environments.

Salary Range- $170,000- $250,000

More about Gatik

Founded in 2017 by experts in autonomous vehicle technology, Gatik has rapidly expanded its presence to Mountain View, Dallas-Fort Worth, Arkansas, and Toronto. As the first and only company to achieve fully driverless middle-mile commercial deliveries, Gatik holds a unique and defensible position in the AV industry, with a clear trajectory toward sustainable growth and profitability.

We have delivered complete, proprietary AV technology - an integration of software and hardware - to enable earlier successes for our clients in constrained Level 4 autonomy.  By choosing the middle mile – with defined point-to-point delivery, we have simplified some of the more complex AV challenges, enabling us to achieve full autonomy ahead of competitors. Given extensive knowledge of Gatik’s well-defined, fixed route ODDs and hybrid architecture, we are able to hyper-optimize our models with exponentially less data, establish gate-keeping mechanisms to maintain explainability, and ensure continued safety of the system for unmanned operations.

Visit us at Gatik for more company information and Careers at Gatik for more open roles.

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Taking care of our team

At Gatik, we connect people of extraordinary talent and experience to an opportunity to create a more resilient supply chain and contribute to our environment’s sustainability. We are diverse in our backgrounds and perspectives yet united by a bold vision and shared commitment to our values. Our culture emphasizes the importance of collaboration, respect and agility.

We at Gatik strive to create a diverse and inclusive environment where everyone feels they have opportunities to succeed and grow because we know that together we can do great things. We are committed to an inclusive and diverse team. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

 

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