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About This Role
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
The Position
At Roche, we are developing the next\-generation of sequencing systems. By accelerating clinical research, streamlining workflows, and expanding assay menus, we are also broadening access to genomic data and lowering barriers to adoption. From robust sample isolation and preparation tools to novel sequencing technology and advanced bioinformatics, we are developing differentiated, highly integrated end\-to\-end solutions for next\-generation sequencing workflows.
Our Workflow Automation R Group, a part of Roche Sequencing Solutions, is focused on enhancing sequencing workflows. We are seeking a highly collaborative Principal Automation Research Engineer to contribute to the research and development of current and future automated platforms, while simultaneously building the tools to democratize key processes and eliminate bottlenecks.
This is a hands\-on, multidisciplinary role focused on solving automation challenges, integrating AI tools to streamline workflows, and tackling the fluidic, mechanical and consumables challenges at the heart of our next\-generation platforms. We are looking for someone who exhibits a high degree of motivation, independence, and resourcefulness to help us develop solutions to our automation challenges in a fast\-paced and collaborative environment.
Core Responsibilities
- You will utilize AI\-assisted coding and modern software development tools to accelerate protocol generation, protocol simulation, debugging, test suite development, and automated error recovery.
- You will translate complex manual workflows (i.e. sample prep, library prep, target enrichment, quantification, pooling, and sequencing) into highly reliable automated scripts.
- You will test scripts and validate system performance through various analytical equipment and data analysis pipelines
- You will contribute to architecture, design, research and development of next\-generation automation platforms. Design, build, assemble and operate custom test fixtures to support testing of these platforms, modules and sub\-systems.
- You will translate high\-level system and assay requirements into fluidic schematics, system architectures and concepts to evaluate, compare, and downselect design paths.
- You will create and maintain comprehensive documentation for all work, from requirements, schematics, diagrams, CAD models, manufacturing drawings, and material specifications.
- You will partner directly with Assay Development Scientists, Hardware Engineers, Software Developers, and Product Managers to align platform functionality with customer requirements. Conduct cross\-functional concept, code/script and design reviews. Present progress, data, and engineering decisions clearly to stakeholders.
This position is based on\-site in Santa Clara, CA. (This is not a hybrid position. There will be some travel to our Roche Pleasanton (CA) site.)
Relocation benefits are not being offered for this role.
Please include a cover letter with your application.
Who You Are:
(Required)
- You have a degree in Bioengineering or Biomedical Engineering, or a closely related discipline, with relevant industry experience (7\+ years for a Bachelor's, 5\+ years for a Master's, or 3\+ year for a PhD).
- You have a demonstrated level of In\-depth understanding of chemistry and molecular biology, specifically sequencing chemistry and workflows
- You have demonstrated hands\-on experience characterizing and testing complex automation systems for sequencing or diagnostics.
- You have demonstrated hands\-on experience using modern AI\-assisted tools to accelerate code generation, parse schemas, and automate test cases.
- You have demonstrated experience with markup and programming languages (e.g., XML, Python, or proprietary scripting environments) used to define automated instrument steps and hardware execution.
- You have a solid level of experience in experimental design
- You have a demonstrated level of proficiency with machine shop tools, measurement equipment, and rapid prototyping technologies.
- You have demonstrated experience troubleshooting, with a solid understanding of physics, chemistry and engineering fundamentals.
Preferred Qualifications:
- You have experience with DNA sequencing, DNA synthesizers and other complex fluidic automation instrumentation.
- You have a demonstrated track record of acting as a bridge between scientists and the hardware/consumables engineers.
- You have excellent organizational skills with the ability to manage multiple project tracks efficiently and thrive in ambiguous, fast\-paced environments.
- You have experience working with a sense of urgency, contagious optimism, and natural curiosity regarding technical, business, and market trends.
- You have demonstrated experience in SolidWorks for part design, detailed assembly design and the creation of manufacturing drawings.
The expected salary range for this position based on the primary location of Santa Clara, CA is $110,600 \- $205,500\. Actual pay will be determined based on experience, qualifications, geographic location, and other job\-related factors permitted by law. We encourage all qualified applicants to apply. The role's level (\& title) may be adjusted based on experience and qualifications. A discretionary annual bonus may be available based on individual and Company performance.
This position also qualifies for the benefits detailed at the link provided below.
Benefits
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life\-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this formAccommodations for Applicants.
Salary Context
This $110K-$205K range is below the median for Research Engineer roles in our dataset (median: $207K across 63 roles with salary data).
View full Research Engineer salary data →Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 4,317 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Roche, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills Required
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $272,100 based on 227 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($158K) sits 42% below the category median. Disclosed range: $110K to $205K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and AI Engineering Manager ($244,000). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Roche AI Hiring
Roche has 1 open AI role right now. They're hiring across Research Engineer. Based in Santa Clara, CA, US. Compensation range: $205K - $205K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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