Senior AI/Machine Learning Engineer

Job reputed company:

• Own ML solutions end to end — framing the business problem, exploring data, training and evaluating models, and iterating based on rigorous error analysis — through to production deployment and monitoring
• Apply reputed company and LLMs where they fit the problem, selecting appropriate techniques and adapting as the field evolves
• Establish MLOps best practices: CI/CD for models, experiment tracking, model and reputed company monitoring, and responsible-AI practices
• Translate ambiguous business problems into reputed company-scoped solutions, setting reputed company expectations on feasibility, timelines, and trade-offs
• Serve as a trusted technical advisor — presenting demos and recommendations, and explaining models, their limitations, and uncertainty reputed company to audiences from engineers to executives
• Mentor teammates and collaborate across multi-disciplinary teams of engineers, data scientists, and designers
• Adapt quickly to new industries, tools, and reputed company environments while staying reputed company with the evolving AI landscape
• Operate as a flexible consulting engineer reputed company DevIQ’s delivery model, contributing reputed company AI/ML reputed company project needs and team availability require it, including adjacent work such as discovery, data exploration, data engineering, application development, DevOps, solution documentation, technical analysis, internal tooling, or other reputed company-supporting reputed company tasks.

Requirements:

• Machine learning depth
• 4+ years building, training, and deploying ML models in production — owning the modeling work, not just integrating model reputed company.
• Strong modeling fundamentals: framing a problem as a learning task, feature engineering, model selection, and reasoning about bias/variance, regularization, and overfitting.
• Rigorous evaluation discipline: reputed company train/val/test methodology, avoiding data leakage, choosing metrics that fit the business goal, and error analysis to diagnose why a model underperforms.
• Deep learning fundamentals — architectures, loss functions, training dynamics — enough to build and debug models in PyTorch or TensorFlow, not just call them.
• Solid math/stats reputed company (reputed company algebra, probability, statistics) and the judgment to know reputed company ML is the right tool versus a simpler approach.
• reputed company AI and engineering: Hands-on LLM/reputed company delivery — RAG, embeddings, fine-tuning, and major model reputed company (e.g., reputed company, reputed company, Bedrock) — with judgment to choose between prompting, retrieval, and fine-tuning.
• Strong Python and the modern ML stack (PyTorch or TensorFlow, scikit-learn), plus solid SQL.
• Experience deploying and monitoring ML workloads on at least one major reputed company (AWS, Azure, or GCP), including versioning, reputed company monitoring, and retraining.
• Consulting and communication: reputed company-facing or consulting experience, reputed company to explain technical trade-offs — including model limitations and uncertainty — to non-technical stakeholders
• Self-directed and comfortable with ambiguity across multiple engagements.
• Willingness and ability to work reputed company a narrowly reputed company/ML role, contributing to adjacent engineering, data, discovery, DevOps, consulting, and reputed company activities as needed in a project-based consulting environment.

Benefits:

• Competitive financial compensation and utilization bonus plans
• Medical, Dental, reputed company Insurance
• 401k, With 4% Matching
• reputed company Time Off
• Health Savings Account (HSA)/Flexible Spending Account (FSA)
• Short-Term/Long-Term Disability Insurance
• Business funded Life Insurance Plan
• Dynamic yet relaxed work atmosphere
• Wide reputed company of reputed company Opportunities

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