Senior - ML Engineer

Summary: The Senior Machine Learning Engineer develops and integrates ML models and NLP solutions on Google Cloud to unlock enterprise data value. This role involves designing scalable data pipelines, training models, and collaborating with cross-functional teams to deliver actionable insights and automate business processes.

General Position Information

Job Title Identification:

Senior Machine Learning Engineer

Reports directly to (Title):

Manager, Data Engineering

Matrix reports to (Title):

As applicable based on functional alignment

Direct Reports:

Individual contributor role, no direct reports

Position Summary:

The Senior Machine Learning Engineer develops and integrates machine learning models and pre-trained APIs within large-scale data ecosystems to help unlock the value of enterprise technology and data platform investments. This role works with structured and unstructured data and partners closely with data scientists, data engineers, clinical teams, operational teams, and business stakeholders to define questions, explore solutions, and deliver actionable insights.

The Senior Machine Learning Engineer designs and deploys innovative machine learning and natural language processing solutions, with a focus on cloud-based technologies and automation. Success in this role requires strong programming and analytical skills, customer-facing communication, collaboration, and a passion for applying emerging machine learning capabilities to meaningful business use cases.

Key Responsibilities:

• Design and develop natural language processing (NLP) and machine learning applications on Google Cloud, including solutions leveraging Vertex AI and Document AI.
• Implement text representation, feature engineering, statistical, and classification techniques to transform natural language data into actionable features and insights.
• Select appropriate datasets, algorithms, frameworks, and tools to support robust model training and business requirements.
• Train, evaluate, and monitor machine learning models; conduct experiments and statistical analysis to improve predictive accuracy, reliability, and performance.
• Integrate structured and unstructured data from multiple sources through APIs and optimize data pipelines for scalability, efficiency, and consistent data flow.
• Develop and deploy machine learning solutions using C#, SQL, Python, cloud platforms, machine learning frameworks, and APIs.
• Partner with cross-functional teams and stakeholders to gather requirements, define business questions, evaluate solution options, and present actionable results.
• Evaluate proof-of-concept solutions considering cost effectiveness, long-term functionality, scalability, and alignment with organizational vision.
• Document methodologies, processes, model findings, and technical solutions to support transparency, knowledge sharing, and repeatability.
• Facilitate workshops and training sessions to build understanding of machine learning concepts and practical applications.
• Stay current on advancements in machine learning and identify opportunities to improve methodologies, automation capabilities, and business solutions.
• Provide technical guidance and assist with the education and development of junior team members in relevant technology areas.

Education & Experience:

• Bachelor's degree in computer science Required; master's degree Preferred.
• 5-8 years of experience as a Data Engineer, NLP/Machine Learning Engineer, or similar role, including experience developing and integrating machine learning models and pre-trained APIs in cloud platforms.

Licenses, Certification & Training Requirements:

N/A

Knowledge, Skills, Abilities, Behaviors:

Must Have Skills:

• Experience developing and integrating machine learning models and pre-trained APIs in cloud platforms.
• Knowledge and expertise in Python and SQL.
• Working proficiency with C#, SQL, Google Cloud Platform technologies such as Vertex AI and BigQuery, and GitHub.
• Deep understanding of text representation techniques, statistics, and classification algorithms.
• Experience with machine learning frameworks and APIs.
• Experience designing, developing, testing, deploying, and maintaining machine learning or application solutions through the full lifecycle.
• Experience integrating structured and unstructured data and optimizing data pipelines.
• Ability to work closely with business and technical stakeholders to understand requirements and translate them into technical solutions.
• Strong communication, collaboration, analytical, and problem-solving skills.

Nice to Have Skills:

• Experience working in healthcare information technology
• Azure DevOps (ADO) experience
• Application development coding, debugging, testing, and production deployment experience
• Experience with Document AI and NLP-focused cloud services

Knowledge, Skills, Abilities and Behaviors:

• Demonstrates strong customer focus and the ability to collaborate with clinical, operational, business, and technical stakeholders.
• Communicates complex technical concepts clearly and presents information in a concise, compelling manner.
• Demonstrates sound judgment, analytical thinking, and effective decision-making when evaluating machine learning approaches and business tradeoffs.
• Builds collaborative relationships and works effectively in a cross-functional, team-oriented environment.
• Provides coaching, mentoring, and knowledge sharing to strengthen team capabilities.
• Demonstrates curiosity, innovation, and a commitment to continuous learning as machine learning technologies evolve.
• Maintains attention to quality, documentation, reliability, and responsible delivery of production solutions.