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About This Role
Location: Pasadena, United States of America
Thales people architect identity management and data protection solutions at the heart of digital security. Business and governments rely on us to bring trust to the billions of digital interactions they have with people. Our technologies and services help banks exchange funds, people cross borders, energy become smarter and much more. More than 30,000 organizations already rely on us to verify the identities of people and things, grant access to digital services, analyze vast quantities of information and encrypt data to make the connected world more secure.Biometrics and AI Research Engineer
Pasadena CA, Hybrid
Applicants must be legally authorized to work in the United States for any employer at the time of hire. This position is not eligible for visa sponsorship or for assuming sponsorship of an employment visa now or in the future.
Regulatory Compliance Requirements
Must be a U.S. Person as defined in applicable law, or otherwise authorized or eligible for authorization, to access to hardware, software, technology or technical data controlled under the Export Administration Regulations (EAR).
Position Summary
As a Biometrics and AI Research Engineer in our Pasadena, California\-based biometrics research organization, you will be working at the intersection of scientific innovation and advanced software engineering. You will translate cutting\-edge research into scalable software solutions while influencing technical direction across research initiatives, collaborating with cross\-functional engineering teams, and contributing to the long\-term technology strategy of our biometric platforms. This position requires deep technical expertise, sound engineering judgment, and the ability to solve complex technical challenges with significant business impact
Key Areas of Responsibility
Research \& Innovation
- Design and execute sophisticated experiments utilizing large\-scale biometric datasets to evaluate algorithm accuracy, robustness, fairness, security, and operational performance.
- Research, evaluate, and implement state\-of\-the\-art machine learning, deep learning, computer vision, and signal processing techniques applicable to biometric recognition systems.
- Benchmark internal technologies against published research, commercial solutions, and industry evaluations to identify opportunities for advancement.
- Identify emerging trends in biometrics, artificial intelligence, and adjacent technologies, recommending adoption where appropriate.
Software Engineering
- Develop high\-quality, secure, production\-oriented software prototypes and research tools using modern software engineering practices.
- Design reusable software components supporting biometric acquisition, feature extraction, matching, fusion, evaluation, and performance analysis.
- Champion software quality through code reviews, automated testing, version control, and secure coding methodologies.
- Collaborate with software engineering teams to transition research innovations into scalable production solutions.
- Make architectural recommendations that influence biometric system design, software frameworks, and algorithm integration.
Cross\-Functional Collaboration
- Partner closely with scientists, software engineers, systems engineers, product management, and program teams to align research priorities with customer and business objectives.
- Provide technical leadership during system integration, ensuring algorithm performance meets operational and customer requirements.
- Support proposal efforts, technology demonstrations, customer engagements, and technical evaluations.
Technical Influence
- Prepare technical publications, invention disclosures, patents, conference papers, and customer presentations supporting organizational innovation.
- Represent the organization at technical conferences, industry working groups, and customer engagements.
Minimum Qualifications
- Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, Artificial Intelligence, Mathematics, or related technical discipline with 5\+ years of relevant industry experience;
- Demonstrated experience leading development of advanced biometric or AI\-based technologies from research through implementation.
- Strong background in machine learning, computer vision, pattern recognition, statistical modeling, or signal processing.
- At least 4 years developing software applications using C/C\+\+ and Python.
- Experience with PyTorch, TensorFlow, ONNX Runtime, OpenVINO, TensorRT, or similar machine learning frameworks.
- Prior experience with biometric applications
- Hands on experience designing experiments, analyzing large datasets, and interpreting statistical performance metrics.
- Strong understanding of software engineering best practices, secure coding, testing methodologies, and source control.
- Demonstrated ability to influence technical direction across multidisciplinary engineering teams.
- Excellent written and verbal communication skills, including presenting complex technical concepts to diverse audiences.
Preferred Qualifications
- Master's in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, or related discipline.
- Experience developing large\-scale biometric identification or authentication systems.
- Expertise in deep learning architectures including CNNs, Vision Transformers (ViT), Graph Neural Networks (GNNs), diffusion models, and multimodal AI.
- Experience optimizing AI models for GPU and edge deployment using CUDA, OpenCL, or equivalent technologies.
- Experience with biometric standards (ISO/IEC 19794, NIST evaluations, FRVT, MINEX, IREX, FpVTE, etc.).
- Knowledge of adversarial machine learning, presentation attack detection (PAD), liveness detection, or biometric security.
- Demonstrated history of technical publications, patents, or conference presentations.
- Experience mentoring engineers or leading technical project teams.
If you’re excited about working with Thales, but not meeting the requirements for this position, we encourage you to join our Talent Community!
Special Position Requirements
Travel: 10%
Why Join Us?
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This position will require successfully completing a post\-offer background check. Qualified candidates with \[a] criminal history will be considered and are not automatically disqualified, consistent with federal law, state law, and local ordinances.
Thales champions inclusion and we believe diversity strengthens the fabric of our culture. Thales is an Equal Opportunity Employer, including disability/veterans.
If you need an accommodation or assistance in order to apply for a position with Thales, please contact us at [email protected].
The reference Total Target Compensation (TTC) market range for this position, inclusive of annual base salary and the variable compensation target, is between
Total Target Cash (TTC) 136,734\.45 \- 227,890\.75 USD Annual
This reflects how companies in a similar industry and geographic region generally pay for similar jobs. This range helps the Company make pay decisions as one data point among many. Where a position falls within this range is also dependent on other factors including – but not limited to – the employee’s career path history, competencies, skills and performance, as well as the company’s annual salary budget, the customer’s program requirements, and the company’s internal equity. Thales may offer additional benefits and other compensation, depending on circumstances not related to an applicant’s status protected by local, state, or federal law.
(For Internal candidate, if you need more information, please raise HR request through MyThales)
Thales provides an extensive benefits program for all full\-time employees working 30 or more hours per week and their eligible dependents, including the following:
- Elective Health, Dental, Vision, FSA/HSA, Voluntary Life and AD\&D, Whole Group Life w/LTC, Critical Illness, Hospital Indemnity, Accident Insurance, Legal Plan, Identity Theft, and Pet Insurance
- Retirement Savings Plan after 30 days of employment with a company contribution and a match, and with no vesting period
- Company paid holidays and Paid Time Off
- Company provided Life Insurance, AD\&D, Disability, Employee Assistance Plan, and Well\-being Program
Salary Context
This $136K-$227K 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 Thales, 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. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($182K) sits 33% below the category median. Disclosed range: $136K to $227K.
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.
Thales AI Hiring
Thales has 1 open AI role right now. They're hiring across Research Engineer. Based in Pasadena, CA, US. Compensation range: $227K - $227K.
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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