Data Scientist III (AI)

Location: United States; this role can be based remotely in the United States. Additional locations include San Francisco, Los Angeles, San Diego, Sacramento, and Anaheim. Occasional business travel may be required.

Annual base salary: $131,700–$219,500.

Company

hirify.global provides enterprise software that connects people, systems, and data to help large organizations accelerate business value and growth.

What you will do

• Design, develop, evaluate, and improve machine learning and applied AI solutions for enterprise business and technical challenges.
• Apply classification, regression, ranking, forecasting, clustering, anomaly detection, embeddings, and LLM-based methods to agentic use cases.
• Evaluate foundation models, prompts, RAG pipelines, fine-tuned models, and agentic behaviors for accuracy, latency, cost, groundedness, and task completion.
• Develop retrieval strategies covering chunking, metadata, embeddings, vector, keyword, hybrid, semantic retrieval, reranking, and context selection.
• Build evaluation datasets, golden test cases, automated quality metrics, reproducible experiments, regression tests, and model quality gates.
• Collaborate with AI Engineering and production teams on model analysis, deployment handoffs, monitoring, lifecycle management, and mentoring less experienced Data Scientists.

Requirements

• 5–9 years of relevant Data Science, Machine Learning, or Applied AI experience.
• Bachelor’s degree in Machine Learning, Statistics, Data Science, Physics, Computer Science, or a related field, or equivalent education and industry experience.
• Strong Python proficiency with Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow, plus SQL and practical data preparation skills.
• Strong knowledge of statistical analysis, experimental design, hypothesis testing, ML validation, classification, regression, ranking, clustering, forecasting, and anomaly detection.
• Practical experience with LLM prompting, embeddings, model comparison, RAG concepts, chunking, retrieval, and reranking.
• Experience with evaluation datasets, automated quality metrics, reproducible ML/LLM experiments, and MLOps/LLMOps practices including versioning, tracking, automation, and monitoring.
• Working knowledge of agentic AI concepts including planning, routing, tool calling, MCP, A2A, and multi-agent patterns.
• Understanding of model latency, throughput, token usage, inference cost, and performance tradeoffs; familiarity with AWS and/or Kubernetes or Red Hat OpenShift.
• Ability to deliver moderately complex AI/ML initiatives, make technical decisions, collaborate cross-functionally, manage priorities, and mentor junior Data Scientists.

Nice to have

• Experience with OpenSearch, Elasticsearch, FAISS, Milvus, pgvector, or similar retrieval platforms.
• Exposure to LangGraph, OpenAI Agents SDK, Google ADK, CrewAI, or comparable agentic frameworks.
• Familiarity with MLflow, Kubeflow, Ragas, DeepEval, OpenJudge, LangSmith, or similar MLOps/LLMOps and evaluation tools.
• Exposure to SFT, LoRA, QLoRA, domain-specific adaptation, vLLM, NVIDIA Triton, quantization, GPU memory, or inference optimization.
• Experience with Python backend APIs, OpenTelemetry, AI observability, AI safety, prompt-injection evaluation, privacy, responsible AI, model governance, forecasting, causal inference, Agile, Jira, or Confluence.
• Master’s degree in a related field.

Culture & Benefits

• Remote and hybrid work options are available for the United States role.
• Occasional business travel may be required.
• Employee compensation includes annual base salary and may include a variable plan and country-specific benefits.
• BMC supports equal opportunity employment and reasonable accommodation during the hiring process.