Java, Graphql, Scala, Kafka, TigerGraph, MLops, Docker, Neo4j, Spark, Python, Kubernetes, AWS, Airflow, pgvector, Qdrant, Go, MLflow, Flink, Neptune, Kubeflow, Milvus

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

Pytorch, Python, Data annotation or labeling systems, Evaluation design and quality measurement

Logistic Regression, Pyspark, Factor Analysis, Sql, Nlp, Predictive Analysis, Cluster Analysis, Python, Statistical Modelling, AWS, LLMs, cloud computing services, Sagemaker, Multivariate Regression

Deep Learning, Machine Learning, Natural Language Processing, Scala, Python, embeddings, large language models, Go, reinforcement learning, Search technologies

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

pruning , Pytorch, Python, evaluation methodology, experiment tracking, DeepSpeed, benchmark design, reproducibility practices, FSDP, quantization, Compression, model optimization

Machine Learning, Apache Airflow, Tensorflow, Pytorch, Docker, Flask, Python, AWS, Apache Spark, Api Development, Deep Learning, Django, Jenkins, Gcp, MLops, FastAPI, Azure, Kubernetes, Computer Vision, Hugging Face Transformers, Ray, Prefect, GitHub Actions, Dask, LangChain, Generative AI, Dagster

Statistical Modelling, Sql, Python, Cluster Analysis, Factor Analysis, Nlp, Pyspark, Predictive Analysis, Logistic Regression, LLMs, Statistical tools and techniques, Multivariate Regression

Computer Vision, Kubernetes, Python, Docker, ML Ops workflows, experiment tracking tools, Airflow, MLflow, TFX, real-time inference systems, distributed training frameworks, model monitoring and observability tools, feature stores, cloud-native ML tools