About the role
- 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.
- 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.
- 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.
- 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
- 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.