Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLMs, NLP, and real-time AI systems
“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and cloud ML
“AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.”
Mid-level AI/ML Engineer specializing in speech, computer vision, and agentic GenAI
“Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.”
Junior Software Engineer specializing in Edge AI and ML deployment
“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”
Senior Software Engineer specializing in AWS data platforms and event-driven systems
“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”
Mid-level Full-Stack Python Engineer specializing in cloud-native payments and data pipelines
Mid-level Robotics Engineer specializing in autonomous navigation and robot perception
Mid-level AI & Machine Learning Engineer specializing in production ML and LLM applications
Senior Software Engineer specializing in Cloud, DevOps, and Infrastructure as Code
Senior Software Engineer specializing in Cloud DevOps & Platform Engineering
Mid-level Software Engineer specializing in AI/ML and full-stack systems
Senior Software Engineer specializing in hybrid cloud, Kubernetes, and MLOps
Mid-level Machine Learning Engineer specializing in GenAI, LLM agents, and MLOps
Intern Machine Learning Engineer specializing in NLP and LLM/RAG systems
Mid-level AI/ML Engineer specializing in NLP, Computer Vision, and Generative AI
Intern AI/ML Engineer specializing in generative AI and multimodal agentic systems
Mid-level Full-Stack Developer specializing in AI-driven FinTech platforms
Junior Software Engineer specializing in data engineering and machine learning
Entry-level Software Engineer specializing in data pipelines and applied AI
Senior Data Engineer specializing in cloud data platforms and big data pipelines
Mid-level AI/ML Engineer specializing in LLM applications and cloud-native systems
“LLM engineer who has shipped production AI systems, including an RFP requirements extraction platform (OpenAI o4-mini + Azure AI Search + FastAPI) achieving 90%+ accuracy and ~5x throughput through grounding, structured outputs, parallelization, and caching. Also partnered with legal/compliance stakeholders at Nexteer Automotive to deliver an AI document comparison tool with traceability and confidence indicators, adopted by non-technical users and saving ~2 FTEs of review time.”
Mid-level AI/ML Engineer specializing in NLP, MLOps, and Generative AI
“Built and deployed a production generative AI chatbot at NVIDIA using LangChain + GPT-3 integrated with internal data sources, cutting response time nearly in half and improving CSAT by ~12 points. Also delivered LLM-driven QA tools by fine-tuning Hugging Face transformer models and deploying via an AWS-based pipeline (Lambda/Glue/S3) with orchestration (Airflow/Step Functions), CI/CD, Kubernetes, and monitoring (MLflow/Splunk/Power BI).”