Job
Description
Bangalore,Karnataka,India Job ID 764972 Join our Team Ericsson’s R&D Data team is seeking a visionary and technically exceptional Principal Machine Learning Engineer to lead the design, development, and deployment of advanced ML systems at scale. This role sits at the strategic intersection of machine learning, data engineering, and cloud-native architecture—shaping the next generation of AI-driven services at Ericsson. As a senior technical leader, you will architect and guide the end-to-end ML lifecycle, from data strategy and engineering to large-scale model deployment and continuous optimization. You’ll partner closely with data engineers, software developers, and product stakeholders, while mentoring a high-performing team of ML engineers. Your work will help scale intelligent systems that power mission-critical R&D and network solutions. Key Responsibilities: Architect and implement scalable ML solutions, deeply integrated with robust and reliable data pipelines. Own the complete ML lifecycle: data ingestion, preprocessing, feature engineering, model design, training, evaluation, deployment, and monitoring. Design and optimize data architectures supporting both batch and streaming ML use cases. Collaborate with data engineering teams to build real-time and batch pipelines using managed streaming platforms such as Kafka or equivalent technologies. Guide the development and automation of ML workflows using modern MLOps and CI/CD practices. Mentor and lead ML engineers, establishing engineering best practices and fostering a high-performance, collaborative culture. Align ML efforts with business objectives by working cross-functionally with data scientists, engineers, and product managers. Stay current with the latest ML and data engineering advancements, integrating emerging tools and frameworks into scalable, production-ready systems. Champion responsible AI practices including model governance, explainability, fairness, and compliance. Required Qualifications: 8+ years of experience in machine learning, applied AI, or data science with a proven record of delivering ML systems at scale. 3+ years of experience in data engineering or building ML-supportive data infrastructure and pipelines. Advanced degree (MS or PhD preferred) in Computer Science, Data Engineering, Machine Learning, or a related technical field. Proficient in Python (preferred), with experience in Java or C++ for backend or performance-critical tasks. Deep expertise with ML frameworks (TensorFlow, PyTorch, JAX) and cloud platforms, especially AWS (SageMaker, Lambda, Step Functions, S3, etc.). Experience with managed streaming data platforms such as Amazon MSK, or similar technologies for real-time ML data pipelines. Experience with distributed systems and data processing tools such as Spark, Airflow, and AWS Glue. Fluency in MLOps best practices, including CI/CD, model versioning, observability, and automated retraining pipelines. Strong leadership skills with experience mentoring engineers and influencing technical direction across teams. Excellent collaboration and communication skills, with the ability to align ML strategy with product and business needs.
