Principal AI Machine Learning Engineer
Irving, TX 75038 US
- Leading the study and transformation of data science prototypes.
- Researching, designing, and implementing appropriate ML algorithms and tools.
- Leading the consolidation and implementation of new concepts and processes in areas including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile.
- Serving as a subject matter expert regarding the latest industry knowledge to improve the organization's systems and/or processes related to Machine Learning, Deep Learning, Responsible AI, Gen AI, Natural Language Processing, Computer Vision and other AI practices.
- Setting the standards for datasets and data representation methods.
- Extending existing ML libraries and frameworks.
- Determining processes and standards for running machine learning tests and experiments.
- Designing, developing, testing, deploying, maintaining, and improving machine learning system software.
- Setting the strategy for ML/AI tools and processes, determining the future needs of the business.
- Partnering with stakeholders across various business units, Enterprise Architects, Governance, Legal Council, Security to define an overall plan for the Registry, model governance and model inventory tracking.
You will need to have:
- Bachelor's degree or four or more years of work experience.
- Six or more years of relevant work experience.
- Advanced knowledge of all aspects of Machine Learning processes, tools, systems.
- Deep understanding and hands on experience with ML Engineering techniques and tools including ML Models measurement techniques, real-time and batch AI processors.
- Hands on experience with modeling platforms and tools like Domino, Jupyter, H2O.ai, DataRobot, Conda, ML Flow
- Deep understanding of and hands on experience with Data wrangling, feature engineering and creating scalable Data pipelines.
- Experience with database technologies like NoSQL, RDBMS, Graph DBs (like Druid, Neo4J), Presto, Hive, MongoDB, Cassandra, PostgreSQL, Teradata. and others
- Experience with designing and implementing complex enterprise systems including logging, monitoring, scheduling, CI/CD pipelining, code repos
- Experience with Google Cloud Platform, AWS or other similar cloud solutions (GCP preferred)
- Proficient in Big Data Technologies, Data Transport (Pulsar/Kafka), Spark, Jupyter/ Python.
- Experience working with languages like Core Java, J2EE, JSP, Servlet, Node.js, Angular, Python, R, Scala, SQL, in UNIX/Hadoop environments
- Expertise with large containerized environments utilizing Kubernetes, Docker, APIGEE and strong understanding of cloud solutions
- Knowledge of Model Development & Management Lifecycle
- Knowledge of computing statistical significance, familiarity with Statistical Model measurements and metrics, ML and DL modelling and other data science techniques
- Understanding of various algorithms
- Scalable distributed training & compute platform.
- Exposure to product-based development methodology is desirable.
- Experience with various agile methodologies and tools: JIRA, Confluence, Gitlab, CICD, etc.
Equal Employment Opportunity We’re proud to be an equal opportunity employer - and celebrate our employees’ differences, including race, color, religion, sex, sexual orientation, national origin, age, disability, and Veteran status. At Our client, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion page to learn more.