Select appropriate datasets and data representation methods to preprocess and engineer features.
Research and implement appropriate machine learning algorithms and tools.
Design, implement, and support tools and workflows to facilitate machine learning experiments, tests, and production deployments.
Transform and convert data science prototypes into machine learning model deployments.
Develop machine learning applications according to business analytical requirements.
Required qualifications, capabilities, and skills
Bachelor’s degree in computer science, information systems, or electrical engineering, or equivalent experience, with at least 3+ years of applied ML engineering experience.
Good understanding of core algorithms, deep neural networks, and LLMs/SLMs. Experience with Azure OpenAI or similar LLM APIs would be a plus.
Experience with NLP and the relevant frameworks and libraries is preferred.
Knowledge of software development processes for machine learning systems with hands on experience with data/feature engineering, training, orchestration, model deployment/serving, model monitoring, and governance utilizing modern ML frameworks, libraries, and tools.
Experience with public cloud technologies, specifically with AWS (Azure would be a plus), and automation processes and tools such as IaC, and CI/CD pipelines.
Working experience with big data, data lakes/data mesh/lake house architectures, and ML data engineering processes, tools & techniques would be a plus.