Machine Learning Engineer Job at XperiencOps Inc, San Francisco, CA

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  • XperiencOps Inc
  • San Francisco, CA

Job Description

XOPS is a fast-growing startup building the future of observability and automation for IT operations. Our platform unifies complex system data to deliver visibility, control, and intelligent workflows across the enterprise, empowering IT teams to manage the entire employee technology lifecycle with precision. As industries embrace AI to automate cars, rockets, and even farming, IT operations remain stuck in the past, reliant on spreadsheets and manual processes. We believe it is time for a change.

At XOPS, we are pioneering autonomous IT operations, freeing teams from tedious tasks and elevating them into strategic leadership roles. Our mission is to drive operational excellence, financial stewardship, and security across the enterprise, while transforming the employee experience. We are just getting started, and we are looking for exceptional teammates to help shape the future.

XperiencOps Inc. is seeking a talented and experienced Machine Learning Engineer with expertise in graph databases to join our innovative team. 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.

Requirements

  • 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.

For this role, the estimated base salary range is between $157,000 - $193,000 USD. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

Benefits

  • Competitive Compensation: Salary, Equity, and 401K
  • Comprehensive Vision, Dental, and Healthcare plans
  • Discretionary Time off Policy (If you need time off, take time off!)
  • 11 Company-paid Holidays
  • Hybrid Work Policy - 3 days in office/2 days remote
  • A chance to be part of a rapidly growing startup and make a real impact!

Job Tags

Holiday work, Full time, Remote job,

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