Machine Learning Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

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 be in charge of developing 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 like Google and Microsoft before and 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 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 in to 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

• MS/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