Machine Learning Engineer IV at INPOSIA Solutions GmbH
United States, , USA -
Full Time


Start Date

Immediate

Expiry Date

31 Oct, 25

Salary

297300.0

Posted On

31 Jul, 25

Experience

7 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Aws, Ml, Azure, Design Patterns, Software, Programming Languages, Software Development, Data Structures, Distributed Systems, Python

Industry

Computer Software/Engineering

Description
  • United States
  • Engineering
  • 16169
    What You’ll Do
    We are looking for a experienced Machine Learning Engineer IV with a background in software development and a deep enthusiasm for solving complex problems.
    On this team you will work with a group of partners and contributors dedicated to designing and implementing a large language model (LLM) platform. This is the platform that powers diverse applications across Avalara, including both internal and externally facing applications. Your responsibilities as a Machine Learning Engineer IV will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features, with a focus on ensuring high availability and quality of service to all of the platform’s customers. You will report to the Director of AI/ML.
    This is a remote opportunity. #LI-Remote
    This role is not eligible for visa sponsorship.
    What Your Responsibilities Will Be

We are looking for engineers who can think quickly, love to learn, and specialize in implementation. Your responsibilities will include:

  • Building on top of the foundational framework for supporting LLM Applications at Avalara
  • Leveraging best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place.
  • Inspiring creativity by researching anding the latest technologies and methodologies in machine learning and software development.
  • Writing, reviewing, and maintaining high-quality code to industry standards, contributing to the project’s.
  • Leading code review sessions to ensure good code quality
  • Documenting solutions in order to maintain a knowledge base and enable Avalara software agents
  • Mentoring junior engineers to encourage a culture of collaboration
  • Maintaining and enhancing, wherever possible, the platform’s operational robustness

What You’ll Need to be Successful
-

Minimum of 7 years work experience building Machine Learning models and deploying them in production environments as part of creating solutions to complex customer problems.

  • Knowledge of and experience with LLMs - like GPT, Claude, LLama and other Bedrock models
  • Proficiency in developing and debugging software with a preference for Python (familiarity with additional programming languages is valued and encouraged)
  • Bachelor’s degree with computer science exposure
  • Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices.
  • Ongoing exposure to technological innovations in AI & ML (esp. GenAI).
  • Expertise in design patterns, data structures, distributed systems, and experience with cloud technologies.
  • Deep experience with and interest in supporting and maintaining mature high availability systems at scale

Pay Range Details
The base pay range(s) below are provided in compliance with state specific laws. Pay ranges may be different in other locations.
Colorado $148,800-$245,600 (annually)
Washington $148,800-$271,500 (annually)
California $148,800-$297,300 (annually)
NYC $164,500-$297,300 (annually)
The pay range above is the general base pay range for you in the state listed. Your actual salary/wage may be based on several factors, such as geographic location, candidate experience and qualifications, market and business considerations. This role is eligible for an annual bonus based on company performance, depending on the terms of the applicable plan and your role.
How We’ll Take Care of You
Total Rewards
In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses.
Health & Wellness
Benefits vary by location but generally include private medical, life, and disability insurance.
Inclusive culture and diversity
Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship.
What You Need To Know About Avalara
We’re defining the relationship between tax and tech.
We’ve already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we’re a billion dollar business - and we’re not slowing down until we’ve achieved our mission - to be part of every transaction in the world.
We’re bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we’ve designed, that empowers our people to win. We’ve been different from day one. Join us, and your career will be too.

Responsibilities
  • Building on top of the foundational framework for supporting LLM Applications at Avalara
  • Leveraging best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place.
  • Inspiring creativity by researching anding the latest technologies and methodologies in machine learning and software development.
  • Writing, reviewing, and maintaining high-quality code to industry standards, contributing to the project’s.
  • Leading code review sessions to ensure good code quality
  • Documenting solutions in order to maintain a knowledge base and enable Avalara software agents
  • Mentoring junior engineers to encourage a culture of collaboration
  • Maintaining and enhancing, wherever possible, the platform’s operational robustnes
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