Machine Learning Research Engineer

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. They are seeking a Machine Learning Research Engineer to bridge applied research and production engineering, designing and shipping advanced machine learning systems that solve high-impact business problems.

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

Requirements:

• 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
• 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