Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety
“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”
Intern Software Engineer specializing in robotics, autonomous vehicles, and embedded AI
“Robotics software engineer with internship experience at John Deere and AeroVironment, working across C++/Python stacks and ROS2-based systems. Drove a proof-of-concept migration from an x86/FPGA target to NVIDIA GPU solutions and helped turn a hackathon prototype into a production-ready, CI/CD-driven build-and-deploy workflow with comprehensive automated testing.”
Staff-level Machine Learning Engineer specializing in LLMs and MLOps for Financial Services
“Machine learning/NLP practitioner at J.P. Morgan who led development of a production RAG system and an entity resolution pipeline for complex financial data. Deep hands-on experience with embeddings (Sentence-BERT), vector search (FAISS/pgvector), LLM fine-tuning (LoRA/PEFT), and rigorous evaluation (human-in-the-loop + A/B testing) backed by strong MLOps on AWS (Docker/Kubernetes, MLflow, Prometheus/Datadog).”
Senior Engineering Manager specializing in cloud security and graph-based data platforms
“Engineering leader at Sysdig Secure who pitched and prototyped a model data platform that initially got rejected, then proved value by migrating the CIEM offering and expanding adoption across multiple verticals. Now owns the CIEM suite plus the broader Sysdig Secure data and reporting platforms, manages 14 direct reports, and also leads a pilot AI team while remaining hands-on weekly.”
Mid-Level Software Engineer specializing in full-stack development, cloud, and data infrastructure
“Software engineer at Fannie Mae (~3 years) working on high-volume loan data pipelines using AWS (SQS/S3), Java listeners, Postgres, and Python/SQL-based data quality validation. Also built a chess data collection system (leveraging experience as an International Master) with robust retry/monitoring, schema-change handling, and idempotent backfills to prevent bad data from reaching downstream systems.”
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”
Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants
“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”
Mid-Level Backend Engineer specializing in REST APIs and AWS
“Backend engineer who built a new REST eligibility service at Barclays that unified siloed account logic (card/loan/deposit) and integrated with web/mobile, ultimately serving millions of users daily. Also built an end-to-end LLM-based pharmaceutical care-plan generation tool in a rapid Columbia startup competition, emphasizing configurable design, strict validation, persistence, and robust error handling.”
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
Mid-level Software Developer specializing in cloud data engineering and MLOps
“Software engineer with strong AWS production experience, including an end-to-end historical backfill system exporting ~10PB of CloudWatch logs into a data lake using Step Functions/Kinesis/Lambda/Firehose/Glue. Emphasizes reliability and operability (DynamoDB checkpointing, monitoring dashboards, CI/CD with canary tests) and has also built customer-facing UI work for the Visa Developer Portal using Angular + Spring Boot, plus React/Redux frontend work.”
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
Senior Full-Stack Python Developer specializing in cloud-native RAG and microservices
Mid-level AI/ML Engineer specializing in recommender systems, fraud detection, and LLMs
Mid-level Full-Stack Java Engineer specializing in scalable microservices and real-time data systems
Senior Full-Stack Engineer specializing in Next.js, React, and TypeScript
Mid-level Full-Stack Developer specializing in cloud-native microservices and FinTech
Junior Software Development Engineer specializing in AWS cloud services and SDN
Mid-level Machine Learning Engineer specializing in NLP, recommender systems, and on-device ML
Software Engineering Intern specializing in backend APIs, Kafka data pipelines, and cloud systems
Senior Software Engineer specializing in AI/ML evaluation and full-stack systems
Mid-level Full-Stack Software Developer specializing in Java microservices and React on AWS
Senior QA Engineer specializing in mobile, API, and test automation