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.
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