Bright Vision Technologies Logo

Bright Vision Technologies

AI Research Engineer (Applied AI)

Posted Yesterday
Be an Early Applicant
In-Office
San Ramon, CA, USA
100K-150K Annually
Senior level
In-Office
San Ramon, CA, USA
100K-150K Annually
Senior level
Design, prototype, and evaluate applied AI solutions across language, vision, recommendation, and structured data. Translate business problems into ML formulations, run rigorous experiments, build production training and inference pipelines, optimize models for accuracy and latency, develop dataset tooling and monitoring, ensure safety and fairness, document findings, mentor engineers, and influence the AI roadmap.
The summary above was generated by AI
Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled AI Research Engineer (Applied AI) to join our dynamic team and contribute to our mission of transforming business processes through technology.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: AI Research Engineer (Applied AI)
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Salary: $100K - $150K
Experience: 6+ years
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are seeking an AI Research Engineer to bridge cutting-edge applied research and production engineering, designing and shipping advanced machine learning systems that solve high-impact business problems. The role blends scientific rigor with practical software engineering, requiring deep understanding of modern ML and deep learning techniques alongside the ability to build robust, scalable, and well-instrumented production pipelines. The ideal candidate stays current with the rapidly evolving AI research landscape, can critically evaluate new techniques for real-world applicability, and is comfortable operating across the full lifecycle from problem framing and experimentation to deployment and continuous improvement.
Key Responsibilities
  • Design, prototype, and evaluate applied AI solutions across natural language, vision, recommendation, and structured data domains.
  • Translate ambiguous business problems into well-scoped ML formulations with clear success metrics and evaluation strategies.
  • Stay current with the latest research in deep learning, large language models, and adjacent areas, and assess applicability to internal use cases.
  • Implement rigorous experimentation workflows including baselines, ablations, and statistically sound evaluation methodology.
  • Build production-quality training and inference pipelines using modern ML frameworks and orchestration tools.
  • Collaborate with ML platform engineers to ensure efficient use of compute, storage, and accelerator resources.
  • Optimize models for accuracy, latency, throughput, and cost based on production requirements.
  • Develop tooling for dataset construction, labeling, validation, and ongoing monitoring of data quality.
  • Partner with product, design, and domain experts to ensure model behavior aligns with user needs and policy requirements.
  • Implement safety, fairness, and reliability evaluations and incorporate findings into model selection decisions.
  • Document research findings, design decisions, and operational characteristics clearly for both technical and non-technical audiences.
  • Mentor engineers on applied ML methodology, evaluation rigor, and responsible deployment.
  • Contribute to internal knowledge sharing, reading groups, and prototype-to-production playbooks.
  • Influence the broader AI roadmap based on research insight, capability gaps, and emerging opportunities.
Required Qualifications
  • Master’s or PhD in Computer Science, Machine Learning, Statistics, or a closely related field; or equivalent applied experience.
  • Six or more years of combined research and applied ML engineering experience.
  • Strong proficiency in Python and modern ML frameworks such as PyTorch or JAX.
  • Hands-on experience training, fine-tuning, and evaluating deep learning models at non-trivial scale.
  • Solid grounding in mathematics, statistics, and the theoretical foundations of modern ML.
  • Experience taking ML models from research prototype to production with appropriate observability and safeguards.
  • Familiarity with distributed training, mixed-precision training, and accelerator hardware.
  • Strong written and verbal communication skills, including ability to explain complex methods clearly.
  • Demonstrated ability to read, evaluate, and adapt techniques from current research literature.
  • Track record of shipping impactful applied AI projects.
Preferred Qualifications
  • Published research at top-tier AI/ML venues.
  • Experience with large language model training, fine-tuning, or evaluation.
  • Familiarity with retrieval-augmented generation, agentic systems, or multimodal architectures.
  • Exposure to responsible AI, model evaluation, and alignment practices.
  • Experience contributing to open-source ML projects.

How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to [email protected]
Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”

Similar Jobs

Yesterday
Hybrid
San Mateo, CA, USA
Senior level
Senior level
Artificial Intelligence • Computer Vision • Software • PropTech
Develop and deploy applied ML and computer vision models to understand technical drawings and specifications. Work on multimodal reasoning across diagrams, text, and structured data, translate research into production within ~1 year, present prior research, and collaborate closely with founders to build customer-impacting solutions.
Top Skills: Computer VisionMachine Learning
9 Days Ago
In-Office or Remote
2 Locations
190K-332K Annually
Senior level
190K-332K Annually
Senior level
Social Media
Lead Responsible AI projects to detect, mitigate, and evaluate bias across GenAI, foundation models, and recommender systems. Collaborate with product and platform teams, deploy fairness interventions at scale, mentor junior engineers, and define technical strategy to align models with Pinterest policies and business metrics.
Top Skills: Foundation Model Fine-TuningGenerative AiLlmsMl FairnessRed TeamingSearch And Recommender SystemsTransformer-Based ModelsTwo-Tower ArchitecturesVlms
Yesterday
In-Office or Remote
4 Locations
152K-242K Annually
Senior level
152K-242K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
Develop AI compiler solutions, optimize GPU programming, build training pipelines, collaborate on integrating AI policies, and conduct rigorous performance benchmarking.
Top Skills: C++Python

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account