Senior Machine Learning Operations (ML Ops) Data Scientist

Job Description

Role Overview:You are a highly skilled and experienced Staff Data Scientist with a minimum of 1 - 3 years of experience in Data Science and Machine Learning, ideally with expertise in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. Your role involves playing a crucial part in the development and implementation of AI solutions, utilizing your technical proficiency. The ideal candidate should possess a deep understanding of AI technologies and hands-on experience in designing and executing cutting-edge AI models and systems. Furthermore, proficiency in data engineering, DevOps, and MLOps practices will be beneficial for this position.Responsibilities:Your technical responsibilities will include:- Develop, deploy, and monitor machine learning models in production environments.- Automate ML pipelines for model training, validation, and deployment.- Optimize ML model performance, scalability, and cost efficiency.- Implement CI/CD workflows for ML model versioning, testing, and deployment.- Manage and optimize data processing workflows for structured and unstructured data.- Design, build, and maintain scalable ML infrastructure on cloud platforms.- Implement monitoring, logging, and alerting solutions for model performance tracking.- Collaborate with data scientists, software engineers, and DevOps teams to integrate ML models into business applications.- Ensure compliance with best practices for security, data privacy, and governance.- Stay updated with the latest trends in MLOps, AI, and cloud technologies.Mandatory Skills:- **Technical Skills:** - **Programming Languages:** Proficiency in Python (3.x) and SQL. - **ML Frameworks & Libraries:** Extensive knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn), data structures, data modeling, and software architecture. - **Databases:** Experience with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB) databases. - **Mathematics & Algorithms:** Strong understanding of mathematics, statistics, and algorithms for machine learning applications. - **ML Modules & REST API:** Experience in developing and integrating ML modules with RESTful APIs. - **Version Control:** Hands-on experience with Git and best practices for version control. - **Model Deployment & Monitoring:** Experience in deploying and monitoring ML models using: - MLflow (for model tracking, versioning, and deployment) - WhyLabs (for model monitoring and data drift detection) - Kubeflow (for orchestrating ML workflows) - Airflow (for managing ML pipelines) - Docker & Kubernetes (for containerization and orchestration) - Prometheus & Grafana (for logging and real-time monitoring) - **Data Processing:** Ability to process and transform unstructured data into meaningful insights (e.g., auto-tagging images, text-to-speech conversions).Preferred Cloud & Infrastructure Skills:- Experience with cloud platforms: Knowledge of AWS Lambda, AWS API Gateway, AWS Glue, Athena, S3, and Iceberg, and Azure AI Studio for model hosting, GPU/TPU usage, and scalable infrastructure.- Hands-on experience with Infrastructure as Code (Terraform, CloudFormation) for cloud automation.- Experience on CI/CD pipelines: Experience integrating ML models into continuous integration/continuous delivery workflows using Git-based CI/CD methods.- Experience with feature stores (Feast, Tecton) for managing ML features.- Knowledge of big data processing tools (Spark, Hadoop, Dask, Apache Beam).Note: EY exists to build a better working world, aiming to create long-term value for clients, people, and society while fostering trust in the capital markets. Utilizing data and technology, diverse EY teams across 150 countries provide trust through assurance and assist clients in growth, transformation, and operations across assurance, consulting, law, strategy, tax, and transactions. EY teams are dedicated to asking better questions to discover new answers for the complex issues of todays world. Role Overview:You are a highly skilled and experienced Staff Data Scientist with a minimum of 1 - 3 years of experience in Data Science and Machine Learning, ideally with expertise in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. Your role involves playing a crucial part in the development and implementation of AI solutions, utilizing your technical proficiency. The ideal candidate should possess a deep understanding of AI technologies and hands-on experience in designing and executing cutting-edge AI models and systems. Furthermore, proficiency in data engineering, DevOps, and MLOps practices will be beneficial for this position.Responsibilities:Your technical responsibilities will include:- Develop, deploy, and monitor machine learning models in production environments.- Automate ML pipelines for model training, validation, and deployment.- Optimize ML model performance, scalability,

Keyskills :
Data ScienceMachine LearningNLPData engineeringDevOpsPythonSQLPostgreSQLMySQLMongoDBCassandraDynamoDBMathematicsStatisticsAlgorithmsRESTful APIsGitAirflowDockerKubernetesAthenaSparkHadoopGenerative AILLMsMLOpsOptimization techniq