Tensorflow, Machine Learning, Pytorch, Opencv, Python, Ocr, Deep Learning, GenAI, LLMs, PIL

Github, Sql, Git, MLops, Docker, Databricks, Kubernetes, Python, Orchestration, Testing, Prefect, R, GitHub Actions, CI/CD pipelines, GitOps, Production Monitoring, Software engineering best practices, Model versioning, Containerisation, Unity Catalog, Lineage

Machine Learning, Kafka, Sql, MLops, Docker, Spark, Python, Kubernetes, AWS, Ai, anomaly detection, Real-time data processing, Time-series forecasting

Github, Jira, Git, Grc, Containers, Release Engineering, CI-CD integrations, SBOM, credential management, diff-based scanning, fingerprinting, secrets scanning, ASPM tooling, RAG retrieval systems, signed builds, SCA, KEV, EPSS feeds, tree-sitter code parsing, Model runtime prompt engineering, GitLab automation, observability tracing

Machine Learning, Sql, Spark, Python, Neural architectures, ML libraries, Regression, Gradient-boosted trees, ranking, Classification, Causal reasoning, Evaluation frameworks

Pytorch, Python, C++, ROS2, reinforcement learning, ML pipelines, Robotic Systems, ML frameworks, ML concepts and evaluation methodologies, VLA models, MLOps tools and practices, anomaly detection

MLops, Spark, Databricks, Python, Kubernetes, AWS, rollback, deployment strategies, experiment tracking, ML infrastructure, versioning, embedding retrieval systems, classical ML models, Ray, LLM agent workflows, reproducible training data, model validation, model registry, Production Monitoring, NLP models

Machine Learning, Databricks, Sql, Python, Deep Learning, Graph Modelling, Knowledge Graphs, Identity Access Graph

Deep Learning, Nlp, Pytorch, Python, AWS, Gcp, Spark, Azure, Kubernetes, embeddings, inference, Video, end-to-end ML systems, Llm, VLM, training pipelines, fine-tuning, generative AI, cloud platforms, Vision, RAG, Production Monitoring, feature engineering, distributed data processing

error analysis , Deduplication, Pytorch, Python, Cloud Storage, Statistical Analysis, data augmentation, model training, model-based labeling, distributed compute, Active Learning, VLMs, Hugging Face LLMs, ablation studies, dataset curation, benchmark evaluation, workflow orchestration, weak supervision, Batch Processing, inference evaluation, synthetic-data generation, Production Monitoring, data-quality measurement, diffusion models, multimodal models