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Vetted Time Series Forecasting Professionals
Pre-screened and vetted.
Puspa Oli
Junior Machine Learning Engineer specializing in NLP, Computer Vision, and FinTech AI
“AI/LLM engineer who has shipped production RAG and agentic systems end-to-end (LangChain/FAISS, OpenAI+Gemini, FastAPI, Docker, Streamlit), focusing on retrieval quality and low-latency performance. Also partnered with a non-technical PM at deepNow to deliver a forecasting + summarization pipeline for daily market insights with iterative prototyping and a simple UI.”
“LLM/RAG engineer at Connex AI who built and deployed a production healthcare agent to extract clinical insights from medical data/notes. Strong focus on real-world reliability—hallucination mitigation (citations, schema validation, confidence thresholds, rejection logic), custom LangChain orchestration (query rewriting, fallback paths), and production evaluation/observability—while collaborating closely with clinical SMEs to ensure clinical fit and time savings.”
Mid-level Data Scientist specializing in GenAI, MLOps, and computer vision for robotics
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and Computer Vision
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
Junior Data Analyst specializing in analytics engineering and forecasting
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
Junior Machine Learning Engineer specializing in Generative AI and LLM agents
Muhammad Murtaza Murtaza
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics
“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”
MUHAMMAD KHUSHAL KHAN
Mid-level Quantitative Developer specializing in low-latency trading systems
“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”
Intern AI/ML Software Engineer specializing in NLP and model serving
Senior Machine Learning Engineer specializing in NLP and production ML systems
Akshay Amudhan
Entry Machine Learning Engineer specializing in quantitative finance and DeFi
“Built and deployed a production RAG chatbot using a vector database + LangChain-orchestrated pipeline, focusing on grounded, context-aware responses. Demonstrates practical trade-off thinking (retrieval quality vs latency/cost), hallucination control, and iterative improvement through logging, manual review, and stakeholder feedback loops.”
Entry AI Engineer specializing in machine learning, computer vision, and data mining
Entry-Level QA Tester specializing in manual and API testing
Intern Machine Learning Engineer specializing in NLP, RAG, and time-series forecasting