Machine Learning Engineer

Job Description:

As a Machine Learning Engineer, you will play a pivotal role in driving the development and implementation of cutting-edge machine learning solutions for our client. Your responsibilities will encompass a wide range of tasks, from leading a small team of machine learning engineers to collaborating with cross-functional teams to deliver impactful solutions. You will be at the forefront of driving innovation and leveraging the power of machine learning to solve real-world problems, drive business growth, and create value.

Key responsibilities:

• Lead and drive machine learning projects from inception to production: build relationships with business partners and cross-functional teams.
• Collaborate with business leaders, subject matter experts, and decision-makers to develop success criteria and optimize new products, features, policies, and models.
• Partner with data scientists to understand, implement, train, and design machine learning models.
• Collaborate with the infrastructure team to improve the architecture, scalability, stability, and performance of ML platform.
• Construct optimized data pipelines to feed machine learning models.
• Extend existing machine learning libraries and frameworks.
• Develop processes, model monitoring, and governance framework for successful ML model operationalization.
• Define objectives for the Machine Learning platform, own the technical roadmap, and be accountable for delivering results.
• Define standards for engineering and operational excellence for running best-in-class ML platforms and continue to improve ML platforms to keep up with the latest innovations.
• Design and implement the best architectural practices in the delivery of data science use cases.

Key skills/knowledge/experience:

• 7+ years of experience in Machine Learning.
• Extensive software engineering experience with strong working experience as a Machine Learning Engineer.
• Bachelor's degree in computer science, computer engineering, or a related engineering field. Masters degree preferred.
• Advanced proficiency with Python, Java, and Scala.
• Strong computer science fundamentals such as algorithms, data structures, multithreading.
• Experience working with Generative AI, using LangChain for Gen AI and techniques like RAG.
• Experience using ML and DL Libraries:XGBoost, SKlearn, Tensorflow or PyTorch
• In-depth experience building solutions using public clouds such as AWS, GCP.
• Experience using ML platforms like SageMaker, H2O, DataRobot, etc.
• Strong knowledge on ML model development life cycle components like containers, batch vs real time inference endpoints, application security testing etc.
• Experience managing relationships in a cross-functional environment with multiple stakeholders.
• Experience with developing and deploying production-grade applications with ML inferences using automation pipeline on cloud.
• Experience working in Agile/ Scrum development process.
• Thought leadership and innovative thinking.
• Excellent communication and collaboration skills.