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Machine Learning Engineer Hybrid Jobs in Milpitas, CA

Voltai

Machine Learning Engineer

Menlo Park, CA · On-site

The Machine Learning Engineer will architect and develop high-performance AI systems, manage large-scale datasets, and translate state-of-the-art research into production-ready code while ...

Omnissa

Staff Machine Learning Engineer

Mountain View, CA · On-site +1

$162K - $342K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems ... Mountain View, CA or Atlanta, GA Location Type: hybrid Travel Expectations: None Education:

Omnissa

Staff Machine Learning Engineer

Mountain View, CA · On-site

$162K - $342K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems ... Mountain View, CA or Atlanta, GA Location Type: hybrid Travel Expectations: None Education:

Spark Tek Inc

Machine Learning Engineer

San Jose, CA · On-site

Spark Tek Inc is seeking a highly skilled Machine Learning Engineer to design and build a low-latency query understanding and intelligent routing system. The role involves working on data modeling ...

MindSource

Machine Learning Engineer

Cupertino, CA · On-site

MindSource is seeking a Machine Learning Engineer to join their Strategic Data Solutions team. The role involves crafting, implementing, and operating analytical solutions that improve security ...

Aven

Machine Learning Engineer

Campbell, CA · On-site

Aven is seeking Machine Learning Engineers who are passionate about building product models from idea to delivery. In this role, you will maintain models in production, build infrastructure for ...

Capital One

Lead Machine Learning Engineer (IC)

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Adobe

Machine Learning Engineer 4

San Jose, CA · On-site

Adobe is looking for a Senior Machine Learning Engineer to help shape the future of agentic AI in the enterprise. In this role, you will design, build, and scale cutting-edge platforms and products ...

Aven

Machine Learning Engineer

Campbell, CA · On-site

We are looking for Machine Learning Engineers who have built product models from idea to delivery. You are passionate about digging into data, cleaning it, analyzing it, generating ideas, and ...

CYNET SYSTEMS

Machine Learning Engineer

San Jose, CA · On-site

$55 - $60/hr

Champion best practices in software engineering and MLOps to ensure the quality, maintainability, and scalability of machine learning systems. * Continuously evaluate and stay current with the latest ...

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All JobsMachine Learning Engineer Hybrid JobsMachine Learning Engineer Hybrid Jobs in Milpitas, CA

Machine Learning Engineer Hybrid information

See Milpitas, CA salary details

$36.7K

$150.1K

$225.5K

How much do machine learning engineer hybrid jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning engineer hybrid in Milpitas, CA is $150,064.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,300.00 and $180,600.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Hybrid vs Data Scientist?

AspectMachine Learning Engineer HybridData Scientist
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops, tests, deploys ML models; collaborates with engineering teamsAnalyzes data, builds models, interprets results; works across departments
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Machine Learning Engineer Hybrid focuses on developing and deploying ML models within engineering environments, often requiring coding and deployment skills. Data Scientists analyze data, build models, and interpret results, often in research or strategic roles. While both roles require strong analytical skills and knowledge of ML, the Engineer Hybrid emphasizes deployment and integration, whereas Data Scientists focus on data analysis and insights.

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For Machine Learning Engineer Hybrid jobs in Milpitas, CA, the most frequently searched job titles are:

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Machine Learning Engineer Hybrid jobs near you

Machine Learning Engineer

Voltai

Menlo Park, CA • On-site

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Voltai is the leading AI company building agentic systems and frontier foundation models for semiconductor and electronics design. The Machine Learning Engineer will architect and develop high-performance AI systems, manage large-scale datasets, and translate state-of-the-art research into production-ready code while collaborating with engineers and researchers.
Responsibilities:
• Architect and develop high-performance AI systems that combine LLMs, retrieval pipelines, and agentic frameworks tailored to semiconductor and electronics design tasks
• Curate, manage, and optimize large-scale training and evaluation datasets, leveraging both synthetic and human-collected data to support foundation model development
• Train, fine-tune, and deploy foundation models, optimizing for latency, accuracy, and cost across diverse deployment scenarios
• Design cutting-edge retrieval and search algorithms for use in engineering documentation, design schematics, datasheets, and other technical corpora
• Build robust evaluation pipelines to measure model performance across tasks such as code generation, schematic synthesis, and long-context reasoning
• Translate SOTA research into production-ready code, working across the full ML stack from paper to GPU.
• Own strategic technical initiatives, collaborating with customers, engineers, and researchers to solve domain-specific problems with measurable impact
Qualifications:
Required:
• Strong programming expertise in Python, C, or Rust, with a focus on writing performant and maintainable code for large-scale AI systems.
• Proficiency in Python and PyTorch: Strong experience in developing and training models using PyTorch
• GPU Programming with CUDA: Hands-on experience optimizing model training and inference on GPUs using CUDA, including custom kernel development
• Distributed Computing Frameworks: Familiarity with tools like DeepSpeed, Accelerate, Unsloth, or Kubeflow for efficient large-scale model training
• Training and Fine-Tuning: Expertise in fine-tuning and quantizing transformer-based models
• Research to Production: Proven ability to translate academic research papers into scalable, production-ready code.
• Experience in AI Research and Development: Background in AI companies or research labs, contributing to significant machine learning projects.
• Understanding of Model Evaluation and Deployment: Experience in evaluating model performance, deploying models into production environments, and monitoring their performance post-deployment.
Preferred:
• Some background in hardware/electronics, gained through professional, academic, or personal projects
• Contributions to open-source initiatives
• Notable awards or publications in leading journals/conferences
• Experience thriving in a fast-paced, hyper-growth startup environment
Company:
AI models for electronics Founded in , the company is headquartered in , , with a team of 11-50 employees. The company is currently Early Stage.

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