Ursus Inc
Machine Learning Engineer
Ursus Inc, Pleasanton, California, United States, 94566
JOB TITLE: Machine Learning Engineer
LOCATION: Pleasanton, CA
DURATION: 4-6 contract to hire
RATE RANGE: $80-$90/hr
SUMMARY:
As a Machine Learning Engineer, you will play a crucial role in developing and implementing machine learning models and algorithms that drive actionable intelligence.
In this role, you will collaborate with cross-functional teams to analyze complex data sets, design and develop machine learning models, and build scalable solutions. You will also be responsible for optimizing and maintaining graph databases, to ensure high performance and efficient data retrieval.
RESPONSIBILITIES: Design, develop, and implement machine learning models and algorithms that leverage graph databases, to solve complex business problems. Analyze and interpret complex datasets to extract meaningful insights and patterns. Collaborate with cross-functional teams to define project requirements and objectives. Optimize and maintain graph databases, focusing on performance and data retrieval efficiency. Ensure the quality and reliability of machine learning models through rigorous testing and validation. Stay updated with the latest advancements in machine learning and graph databases and incorporate them into our products and solutions. Provide mentorship and guidance to junior machine learning engineers. Document and communicate research findings, methodologies, and results to internal and external stakeholders. QUALIFICATIONS:
Ph.D. in Computer Science with expertise in Machine Learning, Graph Theory, and related fields. 5+ years of experience in designing and implementing machine learning models and algorithms, with a focus on graph analytics. Expertise in graph databases, Neo4j preferred, and their query languages (e.g., Cypher). Proficiency in programming languages such as Python or R, as well as machine learning frameworks like TensorFlow or PyTorch. Strong understanding of statistical modeling and data analysis techniques. Experience with big data processing frameworks (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS) is a plus. Excellent problem-solving and analytical skills. Ability to work on complex problems and deliver innovative solutions. Excellent communication and collaboration skills.
IND123
SUMMARY:
As a Machine Learning Engineer, you will play a crucial role in developing and implementing machine learning models and algorithms that drive actionable intelligence.
In this role, you will collaborate with cross-functional teams to analyze complex data sets, design and develop machine learning models, and build scalable solutions. You will also be responsible for optimizing and maintaining graph databases, to ensure high performance and efficient data retrieval.
RESPONSIBILITIES: Design, develop, and implement machine learning models and algorithms that leverage graph databases, to solve complex business problems. Analyze and interpret complex datasets to extract meaningful insights and patterns. Collaborate with cross-functional teams to define project requirements and objectives. Optimize and maintain graph databases, focusing on performance and data retrieval efficiency. Ensure the quality and reliability of machine learning models through rigorous testing and validation. Stay updated with the latest advancements in machine learning and graph databases and incorporate them into our products and solutions. Provide mentorship and guidance to junior machine learning engineers. Document and communicate research findings, methodologies, and results to internal and external stakeholders. QUALIFICATIONS:
Ph.D. in Computer Science with expertise in Machine Learning, Graph Theory, and related fields. 5+ years of experience in designing and implementing machine learning models and algorithms, with a focus on graph analytics. Expertise in graph databases, Neo4j preferred, and their query languages (e.g., Cypher). Proficiency in programming languages such as Python or R, as well as machine learning frameworks like TensorFlow or PyTorch. Strong understanding of statistical modeling and data analysis techniques. Experience with big data processing frameworks (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS) is a plus. Excellent problem-solving and analytical skills. Ability to work on complex problems and deliver innovative solutions. Excellent communication and collaboration skills.
IND123