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Machine Learning Engineer Biotech Jobs in Los Angeles, CA

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

Warnerbros

Senior Machine Learning Engineer

Burbank, CA · On-site

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

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All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Los Angeles, CA

Machine Learning Engineer Biotech information

See Los Angeles, CA salary details

$33.9K

$138.8K

$208.5K

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

As of Sep 2, 2026, the average yearly pay for machine learning engineer biotech in Los Angeles, CA is $138,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,400.00 and $167,000.00 per year, depending on experience, location, and employer.

What does a machine learning engineer do in biotech?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do machine learning engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

What are the key skills and qualifications needed to thrive as a machine learning engineer in biotech?

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

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

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are the most commonly searched types of Machine Learning Engineer Biotech jobs in Los Angeles, CA?

The most popular types of Machine Learning Engineer Biotech jobs in Los Angeles, CA are:

What are popular job titles related to Machine Learning Engineer Biotech jobs in Los Angeles, CA?

For Machine Learning Engineer Biotech jobs in Los Angeles, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Biotech jobs in Los Angeles, CA look for?

The top searched job categories for Machine Learning Engineer Biotech jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Machine Learning Engineer Biotech jobs?

Cities near Los Angeles, CA with the most Machine Learning Engineer Biotech job openings:

Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in Los Angeles, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $138,750 per year, or $66.7 per hour.

Sr. Machine Learning Engineer - Hybrid schedule

Calance US

Los Angeles, CA • Hybrid

$112K - $154K/yr

Full-time

Medical, Dental, Vision, Life

Posted 8 days ago

Job description

We are hiring Sr. Machine Learning Engineer - Hybrid schedule for a Full Time position in Los Angeles or NYC, CA
Sr. Machine Learning Engineer
About the Role
The Senior Machine Learning Engineer is an integral part of the Technology & Information Services team. This role will be responsible for the design, deployment, and optimization of custom workflows using classical machine learning (ML), Natural Language Processing (NLP), and Generative AI techniques to enhance legal and business processes, while designing, building, and optimizing custom machine learning models and workflows to optimize legal and business workflows. This role will be located in our Global Services Office. Please note that this role may be eligible for a flexible working schedule that allows for a hybrid and in-office presence.
Responsibilities & Qualifications
Other key responsibilities include:
Contributing to the entire lifecycle of AI/ML applications including concept, design, test, release, and support
Developing and maintaining robust ML pipelines for training, validation, and model deployment
Working with DevOps or infrastructure teams to manage GPU resources, model serving frameworks, and CI/CD workflows
Evaluating and integrating new research, tools, and frameworks to advance the team s capabilities
Developing ML/GenAI solutions in a professional manner, and in accordance with established deliverable schedules and firm procedures
Protecting and maintaining any highly sensitive, confidential, privileged, financial, and/or proprietary information that retains
We d love to hear from you if you:
Demonstrate proficiency with Python including experience with libraries and frameworks relevant to GenAI application development (e.g., LangChain)
Exhibit proficiency with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), and serving tools (e.g., TorchServe, ONNX, Triton)
Display proficiency in training or fine-tuning language models (e.g., BERT, Llama2, GPT), and their optimization (LoRA, knowledge distillation, pruning, and quantization)
And have:
A bachelor s degree and master s degree in information systems, computer science, engineering, data science, or a related field, preferably
A minimum of five (5) years of experience in industry roles focused on machine learning, applied AI, or data science
A minimum of five (5) years of Python industry experience
A minimum of three (3) years of experience working with agile teams
Experience building and productizing ML models and systems
Estimated Pay Range: 175-195K

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