Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLM, NLP, and MLOps
“AI/ML Engineer with 3+ years of experience spanning RAG pipelines, MLOps, large-scale data workflow automation, and resilient Playwright-based UI automation. At Black Hawk Network and Wipro, they describe shipping production systems with strong observability and compliance controls, including reducing flaky automation failures from 30% to under 2% and automating 3+ TB/day reconciliation workflows.”
Mid-level AI Builder and Data Engineer specializing in GenAI and data pipelines
“Full-stack AI product engineer who personally built ViGenAir, a multimodal system that turns long-form video into ads using FastAPI, React, and agentic scoring. Stands out for handling complex 50GB+ media pipelines, re-architecting systems to eliminate OOM failures, and making opaque AI workflows usable through interactive visual UX that improved trust, speed, and retention.”
Mid Software Engineer specializing in backend microservices and Healthcare IT
“Application-focused full-stack engineer in the clinical/health domain who shipped an LLM-powered clinical note summarization workflow end-to-end (FastAPI + Postgres + Kafka workers + React/TypeScript UI) with strong attention to security, auditability, and clinician trust. Has hands-on AWS/EKS operations experience and has resolved real production latency/scaling issues through async processing, query/index tuning, caching, and horizontal scaling.”
Entry-Level AI/ML Engineer specializing in LLM automation and RAG systems
“AI Automation Engineer at BalancedTrust who single-handedly shipped production LLM features for FinTech compliance: a policy gap-analysis pipeline (SOC 2/GDPR) and a RAG-based regulatory chatbot. Deeply focused on reliability in high-stakes legal/compliance settings, with strong production engineering (edge functions, parallelized batching to cut latency, structured JSON outputs, guardrails, and monitoring) and close collaboration with non-technical compliance experts.”
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
“Data professional with ~4 years of experience, most recently at AIG (insurance), building ML/NLP systems for fraud detection and policy automation using transformers, CNNs, and clustering/anomaly detection. Also developed a RAG-based knowledge retrieval system, iterating across embedding models and moving to production based on precision and latency SLAs, then containerizing and deploying with SageMaker and CI/CD.”
Mid-level AI Engineer specializing in agentic LLM systems and RAG platforms
“Built and shipped Serrano AI, a multi-tenant SaaS conversational AI platform that automates Odoo ERP workflows and lets ops/finance/supply-chain teams query ERP data in natural language. Implemented a multi-agent architecture (LangChain/LangGraph/CrewAI) with hybrid RAG over ERP schemas, deployed on Heroku/Vercel with production observability, cutting reporting time by ~80% while addressing hallucinations, latency, and schema complexity.”
Senior AI/ML & Robotics Research Engineer specializing in SLAM and multi-modal perception
“Robotics engineer who built a smart campus tour robot on a Kobuki Turtlebot using ROS 1, implementing a full navigation stack (semantic world model, A* planner, tour executor, path follower) and integrating SLAM (gmapping) plus a hybrid reactive safety controller. Experienced taking systems from Gazebo simulation to real hardware, including extensive real-world debugging and Docker-based development to handle ROS/Ubuntu version constraints; planning a move to ROS 2 on Turtlebot 4.”
Junior Machine Learning Engineer specializing in GenAI and LLM fine-tuning
“Robotics software engineer focused on hard real-time autonomy for legged robots, building a quadruped navigation stack that combines vision SLAM with MPC and maintains a deterministic 500Hz control loop. Deep performance optimization experience across CUDA (sub-2ms perception latency), ROS 2/DDS real-time tuning, and motion planning (cut 500ms spikes to sub-5ms). Also designed distributed ROS 2 + Zenoh communications between quadrupeds and aerial drones and validated robustness under lossy wireless conditions.”
Mid-level AI/Backend Engineer specializing in RAG and data platforms
“Built and shipped a production LLM-powered financial Q&A interface that extracts precise numeric data from PDFs using a hybrid AWS Textract + LLM normalization pipeline, with confidence gating and guardrails to prevent unreliable answers. Experienced with LangChain-based RAG orchestration (chunking, memory, structured outputs) and collaborated closely with PMs/analysts on IRS Form 990 extraction requirements.”
Mid-level AI/ML Engineer specializing in NLP, fraud detection, and MLOps
“Built and deployed a domain-specific LLM chatbot for research/support, cutting manual effort by ~50%. Demonstrates strong applied LLM engineering: RAG, prompt grounding with citations and fallbacks, embedding/top-k tuning, and production monitoring (confidence, latency, feedback loops). Experienced orchestrating agent workflows with LangChain-style pipelines and continuous evaluation to maintain reliability.”
Junior Software Engineer specializing in full-stack and AI applications
“Full-stack product engineer with hands-on ownership of a B2B e-commerce catalog at Mphasis, spanning React/TypeScript, Java/Spring Boot, and Postgres, with strong evidence of performance tuning and UX improvement. Stands out for tracing production issues across layers, leading an Angular-to-React migration, and pairing product instinct with rapid AI prototyping—placing 2nd in an advanced AI hackathon.”
Mid AI/ML Engineer specializing in LLMs, RAG, and healthcare AI
“Healthcare ML/AI engineer with production experience at UnitedHealth Group, including an end-to-end readmission prediction system built on 50M+ patient records that improved accuracy by 18% and reduced preventable readmissions by 12%. Also shipped a clinically grounded LLM/RAG referral generator with human-in-the-loop safety controls, showing strong depth in regulated, high-stakes AI systems.”
“Built and owned a production RAG-based conversational AI system at Entera for real estate analysis, taking it from experimentation through AWS deployment, monitoring, and iterative improvement. Demonstrates strong practical judgment in retrieval design, LLM safety, and scalable Python service architecture, with measurable impact including 30-40% reduction in manual analysis time and roughly 30% better response accuracy.”
Mid-level Software Engineer specializing in Python backend and AI/GenAI
“Backend/infrastructure-focused engineer building AI-agent products for small businesses, including a customer-service agent platform with intent routing, RAG over Pinecone, and external booking API integration. Has shipped Python/FastAPI services with JWT auth, versioned APIs, Docker deployments to AWS EC2 via GitHub Actions, and production monitoring with Prometheus/Grafana.”
Mid-level Software Engineer specializing in backend systems, microservices, and AI pipelines
“AI/LLM engineer focused on building reliable, scalable multi-agent and RAG-based pipelines across microservices. Stands out for combining practical experimentation with strong engineering discipline around schema validation, retries, observability, and structured API contracts to make LLM systems production-ready.”
Mid Software Engineer specializing in backend, full-stack, and AI systems
“Full-stack engineer with strong fintech/financial-systems experience who built an automated reconciliation and reporting system end-to-end (Python/Django/FastAPI + React, Docker on AWS), cutting reconciliation time by ~25% and improving audit traceability. Experienced designing typed REST APIs and Postgres data models, operating production workloads on AWS (EC2/Lambda/RDS/DynamoDB/CloudWatch), and building reliable ETL/integration pipelines with idempotency, retries, and reconciliation.”
Entry-level AI Engineer specializing in LLMs and applied NLP systems
“Built Lumo, a real-time voice AI companion, owning the product end-to-end across React/TypeScript, FastAPI WebSockets, and PostgreSQL. Stands out for combining deep full-stack systems thinking with voice UX polish, reliability instrumentation, and configurable parent-control guardrails in a multi-tenant setup.”
Mid-level Data Scientist / ML Engineer specializing in Generative AI, RAG, and MLOps
“Built and productionized a RAG-based LLM research assistant for biomedical and regulatory document search using Mixtral 7B on SageMaker, LangChain, and Milvus, cutting research time by ~40%. Has hands-on multi-cloud MLOps experience across AWS/Azure/GCP with Kubeflow/Airflow/Composer plus Terraform + ArgoCD, and applies rigorous evaluation/monitoring (latency, accuracy, hallucinations). Also partnered with a non-technical PM to deliver an insurance policy Q&A chatbot that reduced customer response time by 30%+.”
Mid-level Data Scientist & AI/ML Engineer specializing in GenAI, NLP, and predictive modeling
Mid-level Prompt Engineer specializing in Generative AI and RAG systems
Senior Machine Learning Engineer specializing in GenAI, LLMs, and Python backend
Mid-level AI/ML Engineer specializing in credit risk, NLP, and fraud detection
Junior Full-Stack Software Engineer specializing in scalable web platforms
Intern Full-Stack & AI Engineer specializing in LLM applications and computer vision