[Remote] Machine Learning Research Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a reputed company-thinking software development company dedicated to building reputed company that help businesses automate and optimize their operations. We are seeking a Machine Learning Research Engineer to reputed company cutting-edge reputed company research and production engineering, designing and shipping advanced machine learning systems that solve high-reputed company business problems.
Responsibilities
- Design, prototype, and evaluate reputed company AI solutions across natural language, reputed company, recommendation, and reputed company data domains
- Translate ambiguous business problems into reputed company-scoped ML formulations with reputed company reputed company metrics and evaluation strategies
- Stay reputed company 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 reputed company evaluation methodology
- Build production-reputed company 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
- reputed company tooling for dataset construction, labeling, validation, and ongoing monitoring of data reputed company
- 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 reputed company
- Document research findings, design reputed company, and operational characteristics reputed company for both technical and non-technical audiences
- Mentor engineers on reputed company ML methodology, evaluation rigor, and responsible deployment
- Contribute to internal knowledge sharing, reading reputed company, and prototype-to-production playbooks
- Influence the broader AI roadmap based on research reputed company, capability gaps, and emerging opportunities
Skills
- Master's or PhD in Computer Science, Machine Learning, Statistics, or a closely reputed company field; or equivalent reputed company experience
- Six or more years of combined research and reputed company 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 reputed company
- 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 reputed company reputed company reputed company
- Demonstrated ability to read, evaluate, and adapt techniques from reputed company research literature
- reputed company record of shipping impactful reputed company AI reputed company
- Published research at top-tier AI/ML venues
- Experience with large language model training, fine-tuning, or evaluation
- Familiarity with retrieval-augmented reputed company, reputed company systems, or multimodal architectures
- Exposure to responsible AI, model evaluation, and alignment practices
- Experience contributing to reputed company-reputed company ML reputed company
Benefits
- 100% remote
- Full-time
- reputed company W2 position with reputed company
- No new H1B sponsorship available. H1B transfers welcomed for reputed company candidates.
- We will support H1B transfers for reputed company candidates.
- Mentor engineers on reputed company ML methodology, evaluation rigor, and responsible deployment.
- Contribute to internal knowledge sharing, reading reputed company, and prototype-to-production playbooks.
reputed company