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About This Role
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 Research Scientist – 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.Research Scientist – AI
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Job Title: Research Scientist – AI
Salary Range: 100k$/Annum\-150k$/Annum
Location: 100% Remote (Continental United States)
Position Type: In\-house Bright Vision Technologies SOW engagement (no third\-party client or vendor)
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 boon@bvteck.com or contact us at (908\) 650\-6699\. 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.”
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
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Salary Context
This $100K-$150K range is in the lower quartile for Research Scientist roles in our dataset (median: $183K across 83 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 3,708 AI roles we're tracking, Research Scientist positions make up 3% of the market. At BV Teck, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 197 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($125K) sits 44% below the category median. Disclosed range: $100K to $150K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
BV Teck AI Hiring
BV Teck has 40 open AI roles right now. They're hiring across AI/ML Engineer, MLOps Engineer, LLM Engineer, Research Engineer. Positions span Tempe, AZ, US, Hoboken, NJ, US, Remote, US. Compensation range: $150K - $175K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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