Machine Learning Engineer

Machine Learning Engineer Position Summary Our client is seeking a highly skilled Machine Learning Engineer to design, develop, and deploy robust AI/ML applications that power innovation and deliver actionable insights. In this role, you will collaborate closely with data scientists, software engineers, and product managers to embed advanced machine learning capabilities into products and services. You will be responsible for ensuring scalability, performance, and seamless integration of ML solutions across the organization. Key Responsibilities • Design, build, and maintain production-grade machine learning models and pipelines. • Collaborate with cross-functional teams to translate business needs into ML-driven solutions. • Optimize data pipelines, including preprocessing, feature engineering, and model evaluation. • Deploy and monitor ML solutions in cloud environments, ensuring performance and reliability. • Leverage both relational and non-relational databases to support large-scale data processing. • Stay current with emerging ML techniques, frameworks, and tools. Required Qualifications • 5+ years of proven experience as a Machine Learning Engineer. • Proficiency in Python for ML development and data engineering. • Hands-on experience with RDBMS and NoSQL databases (e.g., BigQuery, MongoDB). • Strong background in data preprocessing, feature engineering, and model evaluation. • Experience working with major cloud platforms (Google Cloud, Azure). • Solid understanding of core ML concepts, workflows, and best practices. Preferred Qualifications • Familiarity with Vertex AI and Azure OpenAI services. • Experience building and deploying LLMs and Retrieval-Augmented Generation (RAG) systems in production. • Knowledge of Natural Language Processing (NLP) techniques and applications. • Experience with Kubernetes (GKE), Docker, and/or DataFlow for ML orchestration. • Exposure to big data frameworks (Apache Spark, Ray, Dask). • Familiarity with streaming data technologies (e.g., Apache Kafka, Pub/Sub). • Proficiency with version control systems (e.g., Git). • Strong problem-solving skills and attention to detail. • Excellent collaboration and communication skills. Education & Certifications • Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field (Master’s preferred). • Relevant certifications (e.g., Google Professional Data Engineer, AWS Certified Data Analytics) are a plus.