Pre-screened and vetted.
Senior Full-Stack & AI/ML Engineer specializing in cloud-native platforms and LLM systems
Mid-level AI Engineer specializing in LLM agents, RAG, and enterprise GenAI
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Mid-Level Software Engineer specializing in cloud-native distributed systems
Mid-level AI/ML Engineer specializing in MLOps, distributed ML, and RAG pipelines
Intern Software Engineer specializing in distributed systems and FinTech
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Senior DevOps / Cloud / Site Reliability Engineer specializing in AWS and Kubernetes
Junior Software Development Engineer specializing in AWS backend and distributed systems
Senior DevOps Engineer / AWS Solutions Architect specializing in Kubernetes and DevSecOps
Mid-level AI Backend Engineer specializing in LLM applications and scalable ML systems
Senior AI Platform Engineer specializing in agentic AI and RAG systems
Senior AI/ML Engineer specializing in GenAI, LLMs, NLP, and MLOps
Senior AI Engineer specializing in LLM agents, RAG, and scalable data platforms
“ML/data engineer who owned an end-to-end production sales analytics pipeline at 15,000+ user scale, delivering ~50% compute reduction, ~80% faster reporting, and ~$1.2M impact. Also shipped a production RAG-based AI assistant over internal BigQuery/docs with evaluation metrics and safety guardrails, and built shared Python libraries to standardize reliability and accelerate engineering teams.”
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
Principal Applied Scientist specializing in ML systems and Generative AI
“Built and owned an end-to-end agentic RAG chatbot platform for Baptist Health that helped clinicians access policy and clinical documents faster, reducing manual lookup by 80% and delivering about $2M in annual savings. Brings strong healthcare GenAI production experience, including HIPAA-aligned governance, PHI redaction, observability, evaluation, and scalable Python/Kubernetes deployment practices.”
“Built and deployed a production RAG-based LLM Q&A and summarization platform for internal documents, emphasizing grounded answers with structured prompting and citations to reduce hallucinations. Experienced orchestrating end-to-end LLM workflows with LangChain plus cloud pipelines (Azure ML Pipelines, AWS), and runs iterative evaluation using both metrics (accuracy/hallucination/latency/cost) and real user feedback to drive reliability.”
Senior DevOps Engineer specializing in AWS cloud platform engineering and Kubernetes
“Cloud-focused DevOps/Infrastructure engineer with hands-on AWS high availability, migration cutovers, and production automation. Built Jenkins-based CI/CD pipelines (Git, SonarQube, Artifactory) and manages Terraform IaC with S3/DynamoDB remote state, PR-based reviews, and staged environment promotion; targets $160k base. No direct IBM Power/AIX/PowerHA experience.”
Mid-level Applied AI Engineer specializing in ML systems, MLOps, and industrial analytics
“Industrial AI/ML practitioner with experience deploying real-time monitoring and anomaly detection in a regulated Sanofi vaccine manufacturing facility, including root-cause workflows, logging/alerting, and SOP-aligned validation—achieving ~90% faster anomaly detection. Also built Python/NLP-style automation to accelerate instrumentation & control documentation (~40% faster) and delivered end-to-end predictive analytics for an agri-food operations/distribution client using close operator and leadership feedback loops.”