Pre-screened and vetted.
Mid-level Data Scientist specializing in NLP, LLMs, and cloud ML platforms
“LLM/MLOps engineer who has shipped production systems for complaint intelligence and contact-center NLU, including LoRA/RLHF-tuned LLaMA models deployed on GKE with vLLM and Vertex AI batch pipelines to BigQuery. Demonstrates strong practical focus on hallucination control, data imbalance mitigation, and production monitoring (Langfuse) with regression testing and canary rollouts, plus experience orchestrating complex workflows with AWS Step Functions.”
Mid-level AI/ML Engineer specializing in GenAI, RAG, and enterprise data platforms
“Built and shipped a production LLM-powered RAG assistant for enterprise internal document search (PDFs, knowledge bases, structured data), addressing real-world issues like noisy documents, hallucinations, and latency with grounded prompting, retrieval-confidence fallbacks, and performance optimizations. Also partnered with compliance and business teams at JPMc to deliver a solution aligned with regulatory constraints, supported by monitoring, feedback loops, and systematic evaluation.”
Mid-level Data Scientist/Data Engineer specializing in ML pipelines, insurance and healthcare analytics
“Built a production assistive-vision iPhone app to help visually impaired users find grocery items, training a custom YOLO detector on 2,000+ self-collected/annotated images and deploying via CoreML with a cloud multimodal LLM for navigation instructions. Brings hands-on AWS serverless + ECS container deployment (CDK/GitHub Actions) and a disciplined approach to AI workflow reliability (state-machine design, offline evals, stress tests, logging/metrics), plus experience communicating model insights to non-technical stakeholders (MOTER Technologies).”
Senior AI/ML Engineer specializing in LLMs, GenAI, and MLOps
“AI/ML engineer (Cognizant) who built a production, real-time credit card fraud detection platform combining deep-learning anomaly detection with an LLM-based explanation layer. Strong focus on regulated deployment: addressed class imbalance and feature drift, and added guardrails (SHAP/structured inputs, fine-tuning on analyst reports, rule-based validation) to keep explanations accurate and compliant. Orchestrated the full pipeline with Airflow + Databricks/Spark and used MLflow/Prometheus plus A/B and shadow deployments for measurable reliability.”
Mid-level Data Scientist specializing in machine learning and generative AI
“ML/LLM engineer who has shipped a production transformer-based document understanding system on AWS, owning the full pipeline from domain fine-tuning to Dockerized CI/CD deployment. Demonstrates strong production rigor—latency optimization (distillation/quantization, async batching, autoscaling), orchestration with Airflow/Step Functions/Azure Data Factory, and monitoring/drift detection—plus experience translating ops stakeholder needs into adopted AI automation via dashboards.”
Mid-level Data Scientist specializing in risk, forecasting, and segmentation across finance and healthcare
“Data/ML engineer with experience across pharma (Dr. Reddy Laboratories) and financial services (Cincinnati Financial, Capital One), building production NLP and entity-resolution systems that connect messy unstructured text with enterprise SQL data. Delivered semantic search with BERT + vector DB and domain fine-tuning (reported ~35% relevance lift), and builds robust pipelines using Airflow/dbt/Spark with strong validation, monitoring, and stakeholder-aligned rollout practices.”
Director-level Technology Leader specializing in data platforms, AI, and media/AdTech transformation
“Technology leader who built a unified platform for Fox live sports production operations starting in 2019, delivering an initial operational system on an ~18-month timeline while simultaneously scaling an in-house engineering team from a service-provider partnership. Led a security architecture for external vendors/partners using a separate Okta instance with zero-trust and passwordless authentication, and drove adoption through strong change management, documentation, and agile execution.”
Senior Engineering Manager specializing in data platforms, microservices, and enterprise GTM analytics
“Engineering leader (player-coach) recently at Autodesk driving a major sales-motion transformation spanning account hierarchy, commissions/quotas, and downstream financial/sales forecasting impacts. Led cross-functional design with enterprise architects and shipped the end-to-end release, using POCs and Anaplan what-if modeling to validate a risky hierarchy change while coordinating delivery across India/Singapore teams and instituting structured Jira-based tech debt/support tracking and automation (dbt, GitHub Copilot).”
Mid-level MLOps/DevOps Engineer specializing in cloud automation and ML pipelines
Mid-level Data Scientist specializing in fraud detection, NLP/LLMs, and MLOps
Junior Software Engineer specializing in Python full-stack, cloud/DevOps, and AI/ML
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG systems
Mid-Level Data Engineer specializing in cloud data platforms and streaming analytics
Mid-level AI/ML Engineer specializing in NLP/LLMs and real-time data pipelines
Mid-level AI Engineer specializing in Ambient AI and full-stack applications
Mid-level Python Backend Developer specializing in cloud-native APIs and data pipelines
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and GenAI
Mid-level Full-Stack Engineer specializing in cloud-native microservices and AI/ML
Mid-level Software Engineer specializing in AI backend, distributed systems, and GPU inference
Mid-Level Software Engineer specializing in FinTech backend and distributed systems