Machine Learning Engineer at MixMode

Job Title: Sr. Machine Learning Engineer
Location: Santa Barbara, CA or Remote within U.S.A.

Job Summary:

MixMode is at the vanguard of a new class of patented Artificial Intelligence based Cyber Security technology. As a Senior Machine Learning Engineer on the AI Team, you will be responsible for designing, building, and maintaining a big-data streaming application that applies our patented AI algorithm to petabyte-scale data. In this role you will work with a team of experienced AI Engineers, Data Engineers, and ML-Ops engineers to design and build novel ML and engineering solutions to big data analytics problems.

Responsibilities:

• Architect, design, and implement Machine Learning applications that run on streams of petabyte-scale data.
• Work with industry leading researchers to invent and build novel algorithms for timeseries analysis
• Architect and build service-oriented solutions for machine learning applications
• Keep current on the latest ML research relevant to our business domain
• Conduct exploratory data analysis and interpret results

Qualifications:

• 5+ years of experience with Python
• Professional experience with a JVM language: Java, Scala, or Kotlin (preferred)
• 5+ years of experience using Machine Learning and data analysis libraries like pytorch, scikit-learn, pandas, etc.
• 3+ years of experience building scalable applications with Kubernetes
• 3+ years of experience with big data tools (Spark, Hadoop, Dask, RedShift, etc.)
• Experience using streaming tools like Flink, Spark Streaming, or similar (preferred)
• 5+ years of experience with relational database tools like Postgres, MSSQL, etc.

Pursuant to California law, we must display the pay range for this job. Since we are willing to hire within a broad spectrum of qualifications, we also reflect a broad pay range.  The base salary range that we are targeting for this position is $160,000 - $210,000 per year, though we can adjust based on individual qualifications. Individual salary is determined by qualifications, role, level, and location.