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Machine Learning Engineer Biotech Jobs in Sacramento, CA

AI Engineer Job Location: Woodland - California Job Type: Contract ... Design develop and deploy machine learning models and algorithms using Python Lead data science ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

Programming using C, C++, and/or Python. * Machine learning and/or deep learning development. * AI framework usage including TensorFlow and/or PyTorch. * Reinforcement Learning and/or Generative AI ...

Programming using C, C++, and/or Python. * Machine learning and/or deep learning development. * AI framework usage including TensorFlow and/or PyTorch. * Reinforcement Learning and/or Generative AI ...

Showing results 21-40

Machine Learning Engineer Biotech information

See Sacramento, CA salary details

$33.6K

$137.3K

$206.3K

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

As of Aug 26, 2026, the average yearly pay for machine learning engineer biotech in Sacramento, CA is $137,309.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,200.00 and $165,300.00 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 popular job titles related to Machine Learning Engineer Biotech jobs in Sacramento, CA?

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

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

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

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

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

Infographic showing various Machine Learning Engineer Biotech job openings in Sacramento, CA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $137,309 per year, or $66 per hour.

Generative AI Engineer III - State and Local Government with Security Clearance

Deloitte

Sacramento, CA • On-site

$61.25 - $82.25/hr

Other

Re-posted 4 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 152 rated financial services


Job description

Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. Work you'll do As an AI and Data Science Engineer III on the team, you will be responsible for: * Design, build, test, and deploy machine learning and artificial intelligence solutions for business and client use cases * Develop and maintain data pipelines, model training workflows, and production-grade application components that support AI-enabled products * Analyze structured and unstructured data to identify patterns, generate insights, and support model development and validation * Collaborate with engineers, data scientists, product stakeholders, and business teams to translate requirements into technical solutions * Monitor model and application performance, troubleshoot issues, and implement enhancements to improve accuracy, reliability, and scalability A successful candidate would possess these skills: * Ability to work independently and collaborate as part of a team * Effective written and verbal communication skills * Meticulous attention to detail and quality of work product * Ability to build and sustain professional relationships * Ability to lead projects or workstreams * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong interpersonal skills and professional demeanor * Ability to meet deadlines * Ability to provide clear guidance to others The team Deloitte's Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise. Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively with organizational intelligence programs and differentiated strategies to win in their chosen markets. Qualifications Required: * Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a quantitative field * 5+ years of professional experience designing, developing, deploying, or supporting machine learning, artificial intelligence, or advanced analytics solutions * 3+ years of experience programming in Python, PySpark, PyTorch, and TensorFlow
* 1+ years of technology consulting experience in the State Government or Local Government space * Active certification in Python, PySpark, PyTorch, or TensorFlow * Ability to travel 20%, on average, based on the work you do and the clients and industries/sectors you serve. * Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future. Preferred: * Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a quantitative field * Ability to obtain and maintain a US government security clearance
* 2+ years of experience deploying machine learning models into production environments * 2+ years of experience working with large language models, natural language processing, or generative artificial intelligence solutions * 2+ years of experience using containerization and orchestration tools such as Docker or Kubernetes * 1+ years of experience supporting model monitoring, model governance, or machine learning operations processes The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $ 110,700 to $218,300. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. ai&e fy27 profile

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