Pre-screened and vetted.
Junior Machine Learning Engineer specializing in LLMs and applied AI
“AI/full-stack engineer with experience spanning startup product building at Twinly, enterprise analytics at Zoho, and high-stakes life sciences ML at Wave Life Sciences. Stands out for combining React/TypeScript + FastAPI product execution with rigorous AI evaluation, retrieval optimization, and human-in-the-loop design, delivering measurable outcomes like 75% fewer analytics requests, 20% fewer failed experiments, and MVP delivery 3 weeks early.”
Executive technology leader specializing in healthcare SaaS and regulated cloud platforms
“Engineering/technology leader who stays hands-on while driving executive-level roadmap execution, with deep experience modernizing cloud-based LIMS/LIS platforms and building AI-driven lab analytics. Led a monolith-to-microservices cloud migration with containerization and CI/CD, and delivered a reported 30% reduction in lab turnaround time while strengthening compliance.”
Mid-level Unity/XR Developer specializing in educational VR and accessibility
“Unity/C# developer from an educational live-service product who spent 5 years shipping across desktop, VR, and mobile while building systems spanning localization, multiplayer, AI-driven avatar experiences, and accessibility. Particularly notable for owning a Lokalise-to-Unity I2 localization backend still in use today and helping lead a major Photon PUN to Fusion migration.”
Mid-level Software Engineer specializing in FinTech and cloud-native systems
“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”
Mid-level AI/ML Engineer specializing in Generative AI and NLP
“AI/LLM engineer with production experience building secure, scalable compliance-focused generative AI systems (GPT-3/4, BERT) including RAG over internal regulatory document bases. Has delivered end-to-end pipelines on AWS with PySpark/Airflow/Kubernetes/FastAPI, emphasizing privacy controls, monitoring, and iterative evaluation (A/B testing). Also partnered closely with bank compliance officers using prototypes to refine NLP summarization/classification and reduce document review time.”
Mid-level Data Engineer specializing in scalable ETL, streaming analytics, and cloud data platforms
“At Dreamline AI, built and productionized an AWS-based incentive intelligence platform that uses Llama-2/GPT-4 to extract eligibility rules from unstructured state policy documents into structured JSON, then processes them with Glue/PySpark and serves results via Lambda/SageMaker/API Gateway. Designed state-specific ingestion connectors plus schema validation and automated checks/alerts to handle frequent policy/format changes without breaking the pipeline, and partnered with business/analytics stakeholders to deliver interpretable eligibility decisions via explanations and dashboards.”
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and MLOps in Financial Services
“ML/LLM engineer at Charles Schwab who built a production loan-advisor chatbot integrated with internal knowledge and loan-calculator APIs, adding strict numeric validation to prevent rate hallucinations and optimizing context to control costs. Also runs ~40 Airflow DAGs orchestrating retraining/ETL/drift monitoring with an automated Snowflake→SageMaker→auto-deploy pipeline, and uses rigorous testing plus canary rollouts tied to business metrics and compliance constraints.”
Senior AI/ML Engineer specializing in Generative AI and agentic systems
“Built and deployed an agentic RAG assistant in production to automate enterprise knowledge search and multi-step workflows with tool calling, tackling real-world issues like hallucinations, retrieval accuracy, and latency. Demonstrates strong LLMOps and orchestration depth (MLflow, Airflow, LangGraph/LangChain/LlamaIndex) plus a metrics-driven approach to agent testing/evaluation and cross-functional delivery with business stakeholders.”
Senior AI/ML Engineer specializing in healthcare and finance AI
“Built production-grade medical AI systems at MD Anderson, including an end-to-end RAG chatbot used by clinical researchers for real-time drug interaction and trial literature queries. Stands out for combining healthcare domain knowledge with strong MLOps, evaluation, and safety practices, and for delivering measurable gains in latency, retrieval precision, and team adoption.”
Mid-level Software Engineer specializing in backend, full-stack, and GenAI for FinTech
“Software engineer with 4 years of experience spanning scalable backend systems, full-stack product development, and production LLM integrations in finance, insurance, and e-commerce contexts. They describe shipping an AI-powered internal financial analysis tool, improving document-review workflows by 40%, and driving a zero-to-one B2B SaaS subscription launch with cross-functional GTM alignment.”
Mid-level Data Scientist specializing in experimentation, NLP, and ML
“Data science and AI professional with Capital One experience building churn prediction and GenAI-powered document intelligence solutions. Stands out for pairing hands-on technical depth in NLP, LLMs, and analytics with strong business communication, including driving adoption across teams and contributing to a 25% reduction in customer churn.”
Mid-level AI/ML Engineer specializing in Generative AI and NLP
“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”
Senior AI/ML & Data Engineer specializing in Generative AI and RAG systems
“GenAI/RAG engineer who has deployed a production policy/regulatory search assistant for a financial client using LangChain + Vertex AI, FastAPI, Docker/Kubernetes, and Airflow-orchestrated data pipelines. Demonstrated measurable impact with 50–60% latency reduction and 70% fewer pipeline failures, plus KPI-driven grounding evaluation (90%+ target) and strong cross-functional collaboration with compliance/business teams.”
“Unity/C# gameplay engineer with unusually broad hands-on range: built a reusable FSM and visual state editor at EA that was applied to AI, meta systems, multiplayer conversion, and console TRC flows, including first-pass Sony/Microsoft/Nintendo certification. Also spans LLM-assisted narrative systems, multiplayer networking, UWP/VR porting, and even arcade hardware/software integration down to designing and hand-building a wiring harness to hit a trade show deadline.”
Mid-Level Software Engineer specializing in backend, cloud, and AI/LLM systems
Mid-Level Software Engineer specializing in Full-Stack, Cloud, and Generative AI/LLMs
Mid-level AI/ML Engineer specializing in risk modeling, NLP, and generative AI (RAG/LLMs)
Mid-level AI/ML Engineer specializing in Generative AI and LLM solutions
Senior Machine Learning Engineer specializing in agentic systems, RAG, and edge AI
Mid-level AI/ML Engineer specializing in NLP, recommender systems, and Generative AI
Senior Data Engineer specializing in cloud data platforms and LLM/RAG solutions
Mid-level AI/ML Engineer specializing in LLMs, RAG systems, and MLOps