Senior Machine Learning Engineer

3 weeks ago


Bengaluru, India EdgeVerve Full time

Job Title: Senior Machine Learning Engineer Experience: 7Yrs to 10Years Location: Bangalore/Pune Key Responsibilities: Machine Learning Model Development: Research, design, and implement advanced machine learning algorithms and models to address business challenges. Data Engineering: Extract, transform, and load (ETL) large datasets from various sources into a Postgres database. Model Deployment: Deploy machine learning models into production environments, ensuring optimal performance and scalability. AI Integration: Integrate AI capabilities into existing systems and applications. Team Leadership: Mentor and guide junior team members in machine learning and data science practices. Problem Solving: Analyze complex business problems and develop innovative solutions using machine learning techniques. Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions Required Skill Set: Technical Skills: Machine Learning: Strong proficiency in machine learning algorithms (regression, classification, clustering, deep learning) and their implementation using Python libraries (TensorFlow, PyTorch, Scikit-learn). AI: Understanding of AI concepts, including natural language processing (NLP), computer vision, and reinforcement learning. Programming: Expert-level Python programming skills, including data manipulation, statistical analysis, and model development. Database: Proficiency in SQL and experience with PostgreSQL for data storage and retrieval. Cloud Platforms: Familiarity with cloud platforms (AWS, GCP, Azure) for deploying and managing machine learning workloads. Data Engineering: Experience with data pipelines, ETL processes, and data preprocessing techniques. Big Data: Knowledge of big data technologies (Hadoop, Spark) is a plus. Soft Skills: Problem Solving: Ability to analyze complex problems and develop effective solutions. Communication: Excellent communication skills to explain technical concepts to both technical and non-technical audiences. Collaboration: Strong teamwork and interpersonal skills to work effectively with cross-functional teams. Leadership: Ability to mentor and guide junior team members. Business Acumen: Understanding of business objectives and how machine learning can drive business value. Continuous Learning: Passion for staying updated with the latest advancements in machine learning and AI.



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