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    Senior Machine Learning Engineer - Los Angeles, United States - FreeForm

    FreeForm
    FreeForm Los Angeles, United States

    1 month ago

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    Description
    SENIOR MACHINE LEARNING ENGINEER

    Freeform is deploying software-defined, autonomous metal 3D printing factories around the world, bringing the scalability of software to physical production. Our proprietary technology stack leverages advanced sensing, real-time controls, and data-driven learning to produce digitally-verified, flawless parts at unprecedented speed and cost. Our mission is to make the transformative power of 3D printing available to all industries at scale and unlock the future of innovation.

    As a Senior Machine Learning Engineer at Freeform, you'll need extensive experience in advanced pattern recognition, predictive modeling techniques, and deep learning algorithms, and should have experience with machine learning as it relates to physics or the physical world. You will play a key role in designing, developing, and integrating critical data science infrastructure and developing custom machine learning algorithms from scratch. Ultimately your solutions with enable us to scale the first production-scale, high-quality, and fully-automated metal 3D printing factory architecture. As a crucial member of the engineering team you will be responsible for driving the pace of innovation, maximizing development speed, and maintaining a standard of excellence within the entire engineering team.

    3D printing experience is not required to be successful here - rather we look for smart, motivated, collaborative engineers who love solving hard problems and creating amazing technology

    Responsibilities:
    • Design and develop data models used for model predictive control in an advanced production-scale metal 3D printing system
    • Integrate data models and physics-based models into a unified simulation framework
    • Develop a deep learning framework for modeling the complex physics associated with laser melting printing technology
    • Develop unsupervised learning algorithms to correlate data with printed part quality
    • Develop methods to correlate process data with geometric features
    • Work closely with simulations engineers to create data models to be used to predict the thermo-mechanical response of printed parts
    • Develop learning modules for machine health monitoring
    • Work with software engineers to deploy data science algorithms in production software
    • Guide software engineers to develop the big data infrastructure required to collect and process large amounts of production printing data
    • Develop data models used for the end-to-end automation of an advanced metal 3D printing platform
    Basic Qualifications:
    • Bachelor's degree in computer science, applied mathematics, machine learning, data science, or similar technical discipline
    • 5+ years of experience in advanced machine learning
    • Proficient with Python, C/C++ or similar object oriented language
    • Proficient in advanced pattern recognition, predictive modeling and deep learning techniques
    • Experience with machine learning or data science as it relates to physics or the physical world
    Nice to Have:
    • Master's or PhD in computer science, applied mathematics, machine learning, data science highly preferred
    • Experience with computational geometry
    • Proficient in data mining and statistical analysis
    • Experience with both supervised and unsupervised learning techniques
    • Experience with image processing
    • Proficient with NoSQL databases, such as MongoDB or Cassandra
    • Experience using query languages such as SQL or Hive
    • Knowledge of MATLAB
    • Creative thinker able to apply first-principles reasoning to solve complex problems
    • Excellent verbal and written communication skills
    Location:
    • We are located in Hawthorne, CA in a 35,000 square foot, state-of-the-art facility featuring large open spaces for team collaboration, R&D, and production, as well as easy access to the 405, 105, and 110 freeways. Our facility is in the heart of Los Angeles' vibrant emerging tech ecosystem alongside many other high growth startups and enterprises.
    What We Offer:
    • We have an inclusive and diverse culture that values collaboration, learning, and making deliberate data-driven decisions.
    • We offer a unique opportunity to be an early and integral member of a rapidly growing company that is scaling a world-changing technology.
    • Benefits
      • Significant stock option packages
      • 100% employer-paid Medical, Dental, and Vision insurance (premium PPO and HMO options)
      • Life insurance
      • Traditional and Roth 401(k)
      • Relocation assistance provided
      • Paid vacation, sick leave, and company holidays
      • Generous Paid Parental Leave and extended transition back to work for the birthing parent
      • Free daily catered lunch and dinner, and fully stocked kitchenette
      • Casual dress, flexible work hours, and regular catered team building events
    • Compensation
      • As a growing company, the salary range is intentionally wide as we determine the most appropriate package for each individual taking into consideration years of experience, educational background, and unique skills and abilities as demonstrated throughout the interview process. Our intent is to offer a salary that is commensurate for the company's current stage of development and allows the employee to grow and develop within a role.
      • In addition to the significant stock option package, the estimated salary range for this role is $140,000-$250,000, inclusive of all levels/seniority within this discipline.
    • Freeform is an Equal Opportunity Employer that values diversity; employment with Freeform is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.

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