Job Description – Sr ML Operations Engineer

Interested in applying your wealth of technical knowledge and experience towards an opportunity in the medical field and improving the lives of people with diabetes?  The candidate will be responsible for building machine learning and artificial intelligence products and has exceptional skills and experience in productionizing machine learning and AI models.

The candidate will be working with other data engineers, data analysts and data scientists to focus on applying data engineering, data science and machine learning approaches to solve business problems. As a senior member of the Data Engineering & Analytics team, you will be building machine learning and artificial intelligence products to uncover customer, product and operational insights.

The candidate should have a passion for software engineering to help shape the direction of the team. Highly sought-after qualities include a self-starter, versatility and a desire to continuously learn, improve, and empower other team members. Candidate will support building scalable, highly available, efficient, and secure software solutions for big data initiatives.

Responsibilities

Designing, architecting and developing machine learning and deep learning systems and platforms.Support the AI Ops needs of data science & software engineering teams from multiple productsCustomize large language models for product applications, and knowledgeable in natural language processing and generative AILead design and coding of big data and machine learning systemsCollaborate with product stakeholders to ideate and prove viability of machine learning use casesTranslate business needs and goals into an AI approach and solution, and articulate findings to a non-technical audienceEffective advanced analytics and AI skills with a foundation in programming (e.g. R, python), database environment (e.g. big-data platforms and SQL skills), and dashboard developmentDesign model performance metrics, retraining schedule and testsAssist with deploying models to cloud infrastructure such as AWS and Microsoft AzureCreate software architecture and design documentation for the supported solutions and overall best practices and patternsProvide architecture and technical knowledge training and support for the solution groupsDevelop good working relations with the other solution teams and groups, such as Engineering, Marketing, Product, Test, QA.Mentor other engineers and data scientists, remain aware of new developments in the field, and help build and grow the team

Required Qualifications

Bachelors Degree in Computer Science, Information Technology or other relevant fieldAt least 3 to 8 years of recent experience in ML or ML Ops experience in a production environmentExperience building end-to-end scalable ML infrastructure and data pipelines with cloud platformsStrong programming (e.g. Python / Java / Kotlin) and data engineering skills.Experience building data pipelines for models and analyticsExperience with deploying and managing model endpointsExperience with natural language processing and generative AIExperience in time series data, signal, image, and video processingExperience using the following software/tools:Unsupervised, semi-supervised and supervised learning methodsMachine learning frameworks such as Keras, PyTorch, or TensorflowLibraries such as numpy, scikit-learn, scipy and statsmodelOutstanding analytical and problem-solving skillsPrior experience in the healthcare or other regulated industriesExcellent written, verbal and listening communication skillsComfortable working asynchronously with a distributed teamAbility to work effectively within a team in a fast-paced changing environment