What are the responsibilities and job description for the Lead AI/ML Engineer position at Long Finch Technologies LLC?
Role and Responsibilities
- Develop, deploy, and maintain advanced AI and machine learning models, including Generative AI, LangChain, and NLP solutions.
- Design and implement machine learning algorithms, ensuring they meet outlined goals and integrate effectively into existing applications.
- Utilize Python programming for software development; Java knowledge is a plus.
- Create and maintain comprehensive documentation, including data dictionaries, model documentation, and code documentation.
- Integrate AI/ML models into applications for both batch and real-time processing.
- Collaborate effectively with team members and stakeholders, demonstrating strong verbal and written communication skills.
- Write and optimize complex SQL queries (Hive/PySpark-dataframes) and manage data pipelines.
- Work with NoSQL databases and leverage experience in Big Data ecosystems including Map-Reduce, Hive, Spark (core, SQL, and PySpark), and UNIX shell scripting.
- Utilize GitHub for version control and CI/CD pipelines for automated deployment.
- Navigate AI/ML governance and compliance requirements in regulated industries, if applicable.
Required Skills
- Hands-on experience in building and deploying AI/ML models, including Generative AI, LangChain, and NLP.
- In-depth knowledge of machine learning algorithms, software architecture, and related libraries and frameworks.
- Proficiency in Python programming for software development; Java is a plus.
- Skillful in creating and maintaining detailed documentation, including data dictionaries, model documentation, and code documentation.
- Experience integrating AI/ML into existing applications for batch and real-time processing.
- Effective verbal and written communication skills for collaboration within and outside the team.
- Hands-on experience with complex SQL (Hive/PySpark-dataframes) and optimizing data pipelines.
- Experience with NoSQL databases is a plus.
- Experience in the Big Data ecosystem, including Map-Reduce, Hive, Spark (core, SQL, and PySpark), and UNIX shell scripting.
- Familiarity with GitHub and CI/CD pipelines.
