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Machine Learning Engineer Biotech Jobs in Reno, NV

Sr AI/ML Engineer

Sparks, NV · On-site

$106K - $146K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques ...

Ensure machined parts meet exact engineering specifications detailed on blueprints and engineering ... Capable of learning and utilizing quality inspection software for data input. Qualifications

Ensure machined parts meet exact engineering specifications detailed on blueprints and engineering ... Capable of learning and utilizing quality inspection software for data input. * Expert Knowledge of ...

Showing results 21-40

Machine Learning Engineer Biotech information

See Reno, NV salary details

$31.4K

$128.4K

$192.9K

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

As of Sep 10, 2026, the average yearly pay for machine learning engineer biotech in Reno, NV is $128,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,200.00 and $154,500.00 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 Reno, NV?

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

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

The top searched job categories for Machine Learning Engineer Biotech jobs in Reno, NV are:

Infographic showing various Machine Learning Engineer Biotech job openings in Reno, NV as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $128,391 per year, or $61.7 per hour.

Sr AI/ML Engineer

Sparks, NV • On-site

Sierra Nevada Corporation
Guided Missile and Space Vehicle Manufacturing • 5 - 10K employees

$106K - $146K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz


Job description

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading the development of complex AI/ML systems, driving innovation, and mentoring team members to deliver impactful solutions. In this role, you will oversee the design, implementation, and deployment of scalable AI/ML models for mission-critical aerospace and defense applications. You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives. This position demands advanced technical expertise and the ability to manage high-impact projects in a fast-paced environment.As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

Responsibilities:

  • Exploration & Innovation:
    • Conduct continuous discovery and hypothesis-driven experimentation, rapidly developing prototypes to assess feasibility and potential impact.
    • Partner with business stakeholders to translate non-technical requirements into actionable AI/ML exploration paths.
  • RAG-Focused AI/ML Development:
    • Develop and prototype RAG-based architectures, including embedding pipelines, retrieval strategies, and transformer-based generative components.
    • Explore and validate new approaches for retrieval, indexing, and multimodal document understanding.
    • Apply validation, safety, and explainability practices in support of aerospace/defense requirements.
  • MPC & Real-Time Decisioning Exploration:
    • Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control.
    • Develop signal processing, perception, and planning pipelines supporting MPC control loops.
    • Use GPU acceleration, simulation environments, and HPC resources to support MPC experimentation.
  • Advanced AI/ML Modeling & Technical Leadership:
    • Architect, train, and optimize advanced models including transformers, GANs, RL agents, and real-time systems.
    • Provide technical leadership, mentor engineers, and guide cross-functional teams.
  • Safety, Validation & Integration Support:
    • Develop validation and testing frameworks ensuring compliance with safety and reliability standards.
    • Support integration teams with prototypes, documentation, and technical insights as required.

Qualifications You Must Have:

  • Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
  • 10+ years of experience in a related field.
  • Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 12 years of related experience is required.
  • Higher level relevant degree may substitute for experience.
  • Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic). Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural networks for complex applications.
  • Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments. Led efforts to improve model performance and reliability in production settings.
  • Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
  • Demonstrated experience leading teams or projects, including mentoring junior staff.
  • Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
  • Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
  • Experience designing and optimizing generative AI models including transformers and GANs.
  • Experience building or integrating transformer-based models for retrieval-augmented or hybrid reasoning systems.
  • Proficiency designing embedding, retrieval, or indexing pipelines for large, multi-source datasets.
  • Familiarity with explainable AI (XAI) techniques for safety-critical environments.
  • Hands-on experience with reinforcement learning and real-time systems applicable to MPC.

Qualifications We Prefer:

  • Master's degree + additional years experience, or Ph.D. in Artificial Intelligence, Machine Learning, or a related field.
  • Experience with hardware acceleration technologies (e.g., CUDA, TensorRT) and high-performance computing systems.
  • Background in autonomous systems, robotics, or sensor fusion.
  • Familiarity with Agile/DevOps methodologies for software development.
  • Certifications in AI/ML or related fields, such as AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer.
  • Deep understanding and practical application of Agile/DevOps in large-scale AI/ML projects.
  • Demonstrated experience with reinforcement learning and generative AI models in production or research settings.
  • Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML workloads for performance.
  • Expertise in designing and implementing complex ML pipelines, including clustering, dimensionality reduction, generative modeling, and reinforcement learning, aligned to mission objectives and HMI systems.
  • Skilled in analyzing massive, multi-source datasets and delivering end-to-end autonomy software solutions, from requirements to deployment and maintenance.
  • Working knowledge of hardware acceleration technologies (CUDA, TensorRT), edge AI deployments, and explainable AI (XAI) methods.
  • Exposure to or interest in quantum computing for ML applications.

Essential Functions:


  • Contribute to AI/ML innovation and prototyping projects from exploration through technical feasibility assessment.
  • Support cross-functional engineering teams and integration efforts as needed.
  • Travel occasionally (10-20%) to customer sites, test facilities, or conferences.
  • Work in a hybrid office environment, balancing hands-on research with technical leadership.
  • Ensure compliance with safety, regulatory, and cybersecurity standards for AI/ML systems.

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

Estimated Starting Salary Range: $143,487.14 - $197,294.82. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled.

SNC offers annual incentive pay based upon performance that is commensurate with the level of the position.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

IMPORTANT NOTICE:

This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment. Non-U.S. citizens may not be eligible to obtain a security clearance. The Department of Defense Consolidated Adjudications Facility (DoD CAF), a federal government agency, handles the adjudicative aspects of the security clearance eligibility process for industry applicants. Adjudicative factors which affect the outcome of the eligibility determination include, but are not limited to, allegiance to the U.S., foreign influence, foreign preference, criminal conduct, security violations and illegal drug use.

Learn more about the background check process for Security Clearances.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We're known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation's most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team!

SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.


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