Company

Machina Labs, founded in 2019 by aerospace and auto industry veterans, is a smart manufacturing company based in Los Angeles, California. Enabled by advancements in artificial intelligence and robotics, Machina Labs is developing software-defined factories of the future. The mission of the company is to develop modular manufacturing solutions that can be reconfigured to manufacture new products simply by changing the software. The company is currently working to build the first commercial robotic sheet metal forming machine. Machina Labs is funded and backed by major investors (NVIDIA, Innovation Endeavors and Lockheed Martin) in the field of AI and Deep Tech.

Job Description

As a Machine Learning Engineer and an early member of our small team, you will own a significant portion of our product and the company. You will develop models to accurately predict important process parameters that are used in our production systems. Every second our robots and the sensors generate a tremendous amount of data that needs to be properly captured, stored, analyzed, and modeled to enable new smart manufacturing technologies. These technologies will enable our leading aerospace and automotive customers to make parts faster, cheaper and enable production of parts that weren't possible.

You’ve ideally developed empirical models based on data in information technology companies before and you are now excited to bring the same techniques to underserved industries like the manufacturing. You are also a skilled software developer and can build reliable software that uses your models. This role requires you to follow agile development practices and understand how to implement quality software that is continuously integrated and deployable to our production cells.

The models you build will have different varieties. The data can be both structured or unstructured. You are in charge of properly defining the problems you are solving, capturing the right data, doing experimentations, cleaning data, modeling and deploying your models. One day you might be using regression to predict forces we see in our manufacturing processes and another day you might use neural networks to predict deformation in our parts from scanned parts.

Responsibilities

Work closely with the Engineering team to uncover opportunities for machine learning automation and predictive modeling across all Machina Labs offerings.
Perform data mining to find interesting and impactful data and finally develop, train and deploy models.
Define proper metrics for each project that can tie into the business objective
Perform data cleaning and ETLs to extract relevant features for modeling
Help other members of the team with data analysis and proper interpretation of data
Proper A/B testing of different solutions or models
Build pipeline that supports running multiple machine learning models in parallel in production.
Build monitoring tools to understand the data quality and performance of complex systems.
Empathetically help other engineers grow
Actively participate in the interview process

Qualifications

Bachelor’s, MS or Ph.D. in related fields (Data Science, Computer Science and Machine Learning, Statistics or a quantitative-related field) or equivalent professional experience.
2+ years of experience with machine learning systems, algorithms or applications such as deep learning and time series analysis.
Startup / early product development experience.
Good understanding of fundamental CS algorithms and their scaling behaviors in data structures, algorithms, and software design
Strong programming background, with extensive experience in Python
In-depth knowledge of build/release systems and process
Experience working with data warehouses, data lakes, and ETL
Experience working with big data platforms (Hadoop, Spark, Hive) and orchestration frameworks (Airflow) and analytic environments (Databricks, Sagemaker, Jupyter)
Able to quickly learn new technologies
Experience in fast-paced iterative design and manufacturing environments
Strong communicator who can explain complex topics to both a technical and non-technical audience
Experience solving complex problems with little to no supervision on schedule as an individual or as a member of an integrated team