Pre-screened and vetted.
Junior Data Scientist / ML Engineer specializing in applied ML, data pipelines, and full-stack systems
Senior AI and Full-Stack Engineer specializing in LLM-powered microservices
Senior Software Engineer specializing in GenAI and full-stack enterprise applications
Mid AI/ML Engineer specializing in MLOps, deep learning, and cloud ML systems
Senior Engineering Leader specializing in platform engineering, DevOps, and SRE
Mid-level Full-Stack Engineer specializing in cloud-native enterprise and FinTech systems
Senior Full-Stack AI Engineer specializing in AI products and developer platforms
Director-level Engineering Leader specializing in cloud platforms, AI/ML, and scalable SaaS
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Senior Full-Stack Developer specializing in cloud microservices and enterprise applications
Mid-level AI/ML Engineer specializing in healthcare, risk modeling, and MLOps
“Robotics software engineer who built a ROS Noetic-based perception-to-control stack for a pick-and-place robotic arm, integrating OpenCV/TensorFlow vision with motion planning and PID tuning. Demonstrated strong real-time debugging skills (rosbag, queue/latency fixes) and experience deploying reproducible robotics environments with Gazebo simulation, Docker, and GitLab CI.”
Mid-level Software Engineer specializing in ML, LLM apps, and cloud data systems
“Built a production SQL chatbot for access-log analytics that replaced manual custom report requests with natural-language querying, using LangGraph and a ChromaDB-backed RAG pipeline for grounded, consistent answers. Implemented a privacy-preserving design where the LLM never sees raw customer data (only query metadata) and has experience building multi-agent/tool-calling systems with LangGraph (DeepAgents), including solving sub-agent communication drift via self-reflection.”
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
“Built an LLM-powered academic research assistant for a professor (LangChain + OpenAI + arXiv) focused on synthesizing papers quickly, with emphasis on reliability (ReAct prompting, citation verification) and cost control (caching). Has production MLOps/orchestration experience at Cisco and HCL Tech using Kubernetes, plus MLflow and GitHub Actions for lifecycle management and CI/CD.”
Mid-level AI/ML Engineer specializing in LLMs, GenAI, and NLP
“AI/ML Engineer who built a production RAG-based LLM system for insurance policy documents, turning thousands of messy PDFs into a searchable index using LangChain, Azure AI Search vectors, hybrid retrieval, and FastAPI. Strong focus on evaluation (MRR/precision@k/recall@k, REGAS) and performance optimization (vLLM), with prior clinical NLP experience using BERT-based NER validated on ground-truth datasets.”
Junior Data Scientist specializing in ML, LLMs, and RAG applications
“University hackathon finalist (2nd place) who built CareerSpark, a production-style multi-agent career guidance app in 24 hours using a hierarchical debate architecture with a moderator/judge agent. Has startup internship experience at LiveSpheres AI using LangChain for multi-LLM orchestration, and demonstrates a structured approach to testing/evaluation (golden sets, integration sims, latency/accuracy KPIs) plus strong non-technical stakeholder communication.”
Mid-level Data Scientist specializing in Generative AI and multimodal systems
“Recent J&J intern who built a conversational RAG agent and led a shift from a monolithic model to a modular RAG workflow, cutting response time from several days to under a second by tackling data fragmentation, context retention, and embedding/latency optimization. Also worked on a large (7B-parameter) multimodal VQA pipeline for healthcare research and stays current via NeurIPS/ICLR and open-source contributions.”
Senior Computer Vision & Robotics Engineer specializing in perception and warehouse automation
“Robotics engineer with hands-on experience scaling a multi-vendor heterogeneous warehouse robot fleet, building a distributed “traffic manager” for collision avoidance and real-time rerouting using CBS/MAPF and DCOP-style negotiation. Strong real-time/safety-critical systems background (RTOS, deterministic lock-free multithreading) plus modern perception and simulation tooling (CNN-LSTM/transformers, CARLA/Isaac Sim, VIO/GTSAM, camera-IMU calibration). Startup-oriented and comfortable moving quickly from prototype to production.”