Top 26 Lead machine learning engineer Jobs in Long Beach, Ca

Lead Machine Learning Engineer
Serve Robotics —Los Angeles, CA
- $225,000 - $260,000 a year
- Full-time
- Remote
- Computer Science
- 5 years
- System design
Architect Lead
Capital Group Companies —Irvine, CA
- $201,683 - $342,072 a year
- Full-time
- Computer science
- Azure
- Computer Science
- Health insurance
- Benefits from day one
AI/ML Tech Lead – Generative AI
Robotics Technologies —Rosemead, CA
- HIPAA
- 3 years
- SQL
AI/ML Tech lead with Gen AI
Robotics Technologies —Rosemead, CA
- HIPAA
- 3 years
- SQL
Tech Lead - Data Scientist
Obsidian Security —Newport Beach, CA
- $220,000 - $250,000 a year
- 6 years
- Salesforce
- APIs
Quick Apply
Global Product Lead, Global Business Applied AI
Google —Los Angeles, CA
- $126,000 - $181,000 a year
- Full-time
- Office
- Master's degree
- SQL
12d
Sentinel - Sr. Staff Lead Engineer (GN&C) - 18840
Northrop Grumman —Manhattan Beach, CA
- $166,500 - $249,700 a year
- Overtime
- System design
- Master's degree
- Analysis skills
- Paid holidays
- Disability insurance
Lead Infrastructure Specialist
Eaton —Santa Ana, CA
- $112,000 - $164,000 a year
- On call
- Background check
- Microsoft Outlook
- Windows
- Retirement plan
Principal Lead Systems Engineer
Raytheon —Fullerton, CA
- $118,300 - $224,900 a year
- Full-time
- Engineering
- Data analysis skills
- 8 years
- Paid holidays
- Disability insurance
Embodied AI Lead / Robot Brain Lead
Faraday Future —Los Angeles, CA
- $180,000 - $250,000 a year
- Computer Science
- Doctor of Philosophy
- Mentoring
- Health insurance
- Dental insurance
Workstream Product Development Lead
McCarthy Holdings, Inc. —Los Angeles, CA
- $125,000 - $160,000 a year
- Computer Science
- No experience needed
- Mid-level
9d
Senior Lead Product Manager - Risk Platform
BILL —Los Angeles, CA
- $191,500 - $239,400 a year
- Remote
- System design
- 8 years
- Product management
- Health savings account
- Employee stock purchase plan
Quick Apply
Lead Crypto Engineer
The MITRE Corporation —El Segundo, CA
- Full-time
- Hybrid work
- Computer science
- Computer Science
- 3 years
11d
Google AI Lead Architect
Deloitte —Costa Mesa, CA
- $141,200 - $278,300 a year
- Full-time
- Azure
- Computer Science
- Up to 50% travel
Technical Delivery Lead - Applications, Google Cloud
Accenture —Culver City, CA
- $87,400 - $266,300 a year
- Full-time
- Hybrid work
- 6 years
- Computer Science
- SQL
- Paid holidays
- Disability insurance
12d
AI Solutions Engineering Delivery Lead
PRICE WATERHOUSE COOPERS —Irvine, CA
- $122,500 - $504,500 a year
- Remote
- Azure
- Computer Science
- SQL
- Paid holidays
- Health insurance
Lead Data & Cloud Solutions Senior Engineer (M.S. or Ph.D.)
Exponent Inc. —Los Angeles, CA
- $143,000 - $169,000 a year
- Email
- Azure
- Computer Science
- Office
- 401(k)
Technical Delivery Lead - Data & Agentic Transformation, Google Cloud
Accenture —Culver City, CA
- $87,400 - $266,300 a year
- Full-time
- Hybrid work
- 6 years
- Computer Science
- SQL
- Paid holidays
- Disability insurance
12d
Technology Internal Audit Lead - Product Technology & Trust and Safety
TikTok —Los Angeles, CA
- $102,600 - $209,380 a year
- 5 years
- Office
- Java
- Paid parental leave
- Paid holidays
Lead, Manufacturing Test Engineer
Relativity Space —Long Beach, CA
- $132,000 - $198,000 a year
- Management
- 3 years
- Senior level
- Opportunities for advancement
Quick Apply

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lead machine learning engineer jobs near long beach, ca

Lead Machine Learning Engineer

Serve Robotics -
Los Angeles, CA

Apply Now

Job Details

Full-time
$225,000 - $260,000 a year

Qualifications

AI models
GPU programming
Software engineering
GPU architecture
Software deployment
System performance optimization
Model deployment
Developing large-scale AI models
Model training
System deployment
Neural networks
Machine learning (ML) fundamentals
Distributed computing
Model evaluation
Machine learning frameworks
Python
MLOps

Full Job Description

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.

Responsibilities

Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications

Master’s or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out

Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
Canada - ALL: $177k - $215k CAD

Compensation Range: $225K - $260K

Apply Now

Refine Your Search

lead machine learning engineer jobs in long beach, ca

Lead Machine Learning Engineer

Architect Lead

AI/ML Tech Lead – Generative AI

AI/ML Tech lead with Gen AI

Tech Lead - Data Scientist

Global Product Lead, Global Business Applied AI

Sentinel - Sr. Staff Lead Engineer (GN&C) - 18840

Lead Infrastructure Specialist

Principal Lead Systems Engineer

Embodied AI Lead / Robot Brain Lead

Workstream Product Development Lead

Senior Lead Product Manager - Risk Platform

Lead Crypto Engineer

Google AI Lead Architect

Technical Delivery Lead - Applications, Google Cloud

AI Solutions Engineering Delivery Lead

Lead Data & Cloud Solutions Senior Engineer (M.S. or Ph.D.)

Technical Delivery Lead - Data & Agentic Transformation, Google Cloud

Technology Internal Audit Lead - Product Technology & Trust and Safety

Lead, Manufacturing Test Engineer

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