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Vetted Feature Engineering Professionals
Pre-screened and vetted.
Senior AI/ML Software Engineer specializing in production ML systems
Staff-level Software Engineer specializing in distributed systems and ML infrastructure
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Machine Learning Engineer specializing in ranking, recommendation, and generative AI
Senior Full-Stack Software Engineer specializing in cloud platforms and healthcare data systems
Senior AI/ML Engineer specializing in Generative AI and cloud-native platforms
Senior Applied AI Engineer specializing in enterprise AI and ML platforms
Senior Machine Learning Engineer specializing in Generative AI and NLP
Mid-level Data Scientist specializing in Generative AI and LLM applications
Principal Data Scientist specializing in Generative AI and security analytics
Senior Full-Stack Software Engineer specializing in AI/ML for FinTech & E-commerce
Senior AI/ML Engineer specializing in generative AI and recommendation systems
Senior Full-Stack AI Engineer specializing in generative AI and cloud platforms
Senior AI/ML Engineer specializing in LLM systems and FinTech platforms
Denis Siminiuc
Junior Research Assistant specializing in LLMs, NLP, and data systems
“Software-focused candidate who built a data monitoring pipeline during a hedge fund internship, integrating real databases and an email API to notify teams when data was ready. Comfortable working through legacy/scrappy code and uses LLMs to accelerate comprehension and delivery, with an emphasis on thorough testing and clear communication with stakeholders/customers.”
Vishanth Iyer
Senior AI/ML Engineer specializing in LLMs, multimodal AI, and scalable MLOps
“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”
Brian Gomez
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”
Deepak Guntreddi
Mid-level Full-Stack Developer specializing in Java/Spring Boot and React
“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”
SAI LIKHIT RENIKUNTA
Mid-level Software Engineer specializing in backend systems and AI platforms
“Backend/AI engineer currently at Stripe building Minions, an internal LLM-based developer agent that automates code generation, bug fixes, and PR creation. They combine strong production LLM architecture skills with reliability engineering, having improved routine PR merge times by ~40-45%, lowered post-merge bug rates by 12%, and previously built an invoice-processing pipeline that achieved 91% straight-through processing in a B2B payments context.”