Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in production ML, NLP, and computer vision
Mid-Level Software Engineer specializing in Java microservices and reactive systems
Mid-level AI/ML Engineer specializing in NLP, Computer Vision, and Generative AI
Mid-level AI/ML Engineer specializing in GenAI, MLOps, and big data on cloud platforms
Mid-level Data Engineer specializing in cloud lakehouse and streaming analytics
Senior Infrastructure Platform Architect specializing in hybrid cloud and Kubernetes automation
Senior Software Developer specializing in Python, AWS, and Big Data
Intern Software Engineer specializing in cloud, DevOps, and LLM-powered tooling
Mid-level Full-Stack Python Developer specializing in APIs, microservices, and cloud deployments
Engineering Manager specializing in backend platforms, risk systems, and FinTech
Mid-Level Software Engineer specializing in backend microservices and cloud automation
Entry-level Software Engineer specializing in data pipelines and applied AI
Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare IT
Mid-level Software Engineer specializing in AWS, full-stack development, and AI data systems
“Backend engineer who built a Python-based data profiling/statistics platform processing up to 50M rows and ~300 metrics, using a DAG execution model, multithreading, and smart caching to cut processing time by up to 70%. Also improved PostgreSQL query performance from 12s to 2s via indexing/query rewrites, integrated an LLM (LangChain + OpenAI) for explainable “chat with the pipeline” functionality, and designed an AWS EC2+SQS architecture for scalable, isolated per-user processing.”
Mid-Level Software Engineer specializing in cloud-native systems, automation, and LLM-enabled robotics
“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”
Mid-Level Software Engineer specializing in Python automation, DevOps, and microservices
“Backend-focused engineer who built an internal wiki LLM chatbot end-to-end using FastAPI, Kubernetes, and ChromaDB vector search, including frontend integration. Also has strong DevOps/migration experience—automating large work-item and repo migrations (Jira/FogBugz/ADO on-prem to cloud) via Python scripts, JSON mappings, REST APIs, and validation test suites.”
Senior Data Scientist / ML Engineer specializing in GenAI, LLMs, and NLP
“ML/NLP engineer focused on production GenAI and data linking systems: built a large-scale RAG pipeline over millions of support docs using LangChain/Pinecone and added a LangGraph-based validation layer to cut hallucinations ~40%. Also built scalable PySpark entity resolution (95%+ accuracy) and fine-tuned Sentence-BERT embeddings with contrastive learning for ~30% relevance lift, with strong CI/CD and observability practices (OpenTelemetry, Prometheus/Grafana).”
Junior Software Engineer specializing in cloud developer tools and backend APIs
“Summer intern on AWS Lambda tooling team who shipped Finch support in AWS SAM CLI, adding OS/runtime detection and robust fallback behavior to preserve Docker compatibility across developer environments. Also built an end-to-end RAG system for querying arXiv quantitative finance papers using Postgres/pgvector with two-stage retrieval, citation-grounded prompting, and rigorous evaluation loops driven by IR metrics and user feedback.”
Mid-level Full-Stack Software Engineer specializing in cloud and data platforms
“Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.”
Senior Software Engineer specializing in cloud-native backend and distributed systems
“Backend engineer focused on Python/FastAPI microservices running on Kubernetes (AWS EKS) with strong GitOps/CI/CD ownership (GitHub Actions + ArgoCD). Demonstrated measurable performance wins (p95 latency cut from >1s to <200ms) and production reliability work across Kafka/Redis streaming and cloud-to-on-prem migrations (RDS/S3 to Postgres/MinIO) using parallel validation and checksum-based consistency checks.”
Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and React/Java
“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”