model development , Data Cleaning, Sql, Numpy, Pandas, Python, offline evaluation, time-series data anomaly detection, scikit-learn, field validation, Forecasting, Classification, hybrid ML plus heuristics, Regression, rule-based systems, deployment monitoring, signal validation, drift detection, feature engineering

state estimation , Vision-Language Models (VLMs), Pytorch, Opencv, ROS, Python, Computer Vision, SLAM, Isaac Sim, MuJoCo, Gazebo, TensorRT, LibTorch, RT-2, OpenVLA, Eigen, ?0, ONNX Runtime, Transformers, Motion Planning, perception, ROS2, Imitation Learning

Golang, Jax, Prometheus, Cloudwatch, Grafana, Tensorflow, Pytorch, Python, Java, Scala, MLops, Spark, Keras, Kubernetes, Scalable ML architectures, End-to-end machine learning pipelines, Automated remediation, MLflow, Prediction and drift monitoring, Model hosting, Stream processing pipelines, Big data frameworks, Model versioning, API performance monitoring, Embedding scaling, Feature stores, Data versioning

snowflake , Sql, Emr, Pandas, Machine Learning, BigQuery, Aws S3, Numpy, Python, Redshift, LLM systems, Snorkel, Airflow, WhyLabs, Label Studio, OpenSearch, scikit-learn, dbt, data-quality controls, ICD-10-CM, Glue, pgvector, Arize, Cpt, Evidently, data pipelines, Hcpcs

data engineering , Numpy, Pandas, Pytorch, Python, scikit-learn, ML pipelines

Git, Docker, Machine Learning Algorithms, Sql, Python, Feature engineering, Model evaluation

Tensorflow, Pytorch, Docker, Python, AWS, Sql, Gcp, MLops, Spark, Azure, Kubernetes, Anthropic Claude, Multi-agent frameworks, Azure OpenAI, Agentic AI systems, Mistral, RAG architectures, LLMs, Prompt engineering strategies, Scikit-learn, model deployment, Fine-tuning pipelines, Agentic AI, Llama, RAG, OpenAI, Gemini

Tensorflow, Machine Learning, Pytorch, MLops, Natural Language Processing, Python, Sql, Deep Learning, Vector Databases, Generative AI, Retrieval-Augmented Generation