ZipRecruiter

Log In

1

Machine Learning Engineer Associate Jobs in Davis, CA

Bespoke Labs

Machine Learning Engineer

Sacramento, CA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Deloitte

AI Solutions Architect

Sacramento, CA

$67.25 - $88.50/hr

... Machine Learning Engineer, Microsoft Azure AI Engineer Associate, Microsoft Azure Data Scientist Associate, or Microsoft Azure Solutions Architect Expert The wage range for this role takes into ...

Deloitte

AI Engineer - SFL Scientific

Sacramento, CA · On-site

Work You'll Do As an AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Deloitte

Senior AI Engineer - SFL Scientific

Sacramento, CA

$111K - $153K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Pwc

Data Engineer - Senior Associate

Sacramento, CA · On-site

$77K - $202K/yr

Focused on relationships, you are building meaningful client connections, and learning how to ... Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus ...

Deloitte

AI Data Engineer - Manager

Sacramento, CA · On-site

$122K - $146K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Lead the development of AI models (e.g., machine learning, natural language processing, computer ...

next page

Showing results 1-20

All JobsMachine Learning Engineer Associate JobsMachine Learning Engineer Associate Jobs in Davis, CA

Machine Learning Engineer Associate information

See Davis, CA salary details

$44.9K

$89.3K

$142.7K

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

As of Jun 27, 2026, the average yearly pay for machine learning engineer associate in Davis, CA is $89,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,800.00 and $102,700.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Machine Learning Engineer Associates when deploying models to production?

Machine Learning Engineer Associates often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and addressing issues with model drift after deployment. Collaborating closely with data engineers and software developers is essential to integrate models seamlessly into existing systems. Additionally, balancing model performance with resource constraints and maintaining clear documentation for reproducibility are important aspects of the role. Gaining familiarity with deployment tools and best practices can help overcome these hurdles.

What are Machine Learning Engineer Associates?

Machine Learning Engineer Associates are entry-level professionals who help design, build, and maintain machine learning models and systems. They typically work under the guidance of senior engineers, assisting in data preprocessing, model training, and testing. Their responsibilities may include implementing algorithms, evaluating model performance, and deploying solutions to production environments. This role requires a strong foundation in programming, statistics, and machine learning principles, often acquired through education or internships.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Associate, and why are they important?

To thrive as a Machine Learning Engineer Associate, you need a solid understanding of programming (especially Python), mathematics, and foundational machine learning concepts, typically supported by a relevant degree or coursework. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with version control systems such as Git are essential. Strong problem-solving abilities, communication skills, and a collaborative mindset help you work effectively within technical teams. These competencies ensure you can develop, implement, and improve machine learning models that deliver actionable insights and drive business value.
What cities near Davis, CA are hiring for Machine Learning Engineer Associate jobs? Cities near Davis, CA with the most Machine Learning Engineer Associate job openings:
Machine Learning Engineer Associate jobs near you

Machine Learning Engineer

Bespoke Labs

Sacramento, CA • On-site

Full-time

Posted 9 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

Apply