Senior Machine Learning Engineer
Reports to: VP of Technology
Location: Atlanta, GA
Technology drives us. Armed with automotive’s most extensive data library, PureCars offers search, pay-per-click, site and display retargeting and advertising to help dealerships reach the right consumer with the right vehicle at the right time. Recognized as one of seven Google Premier SMB Partners in automotive, our award-winning technology is flawlessly designed to drive high probability buyers to a dealer’s site, optimize traffic once on their site, and convert those customers in the showroom.
As a machine learning engineer, you will build fast data and machine learning solutions to address unique and complex problems in the automotive industry. PureCars leverages full stack technology solutions including streaming big data, state of the art machine learning, micro-service architecture, distributed computation engines, and intuitive visualizations in the cloud. You will work alongside highly technical peers, with deep domain expertise, and partner with product and business teams to deliver game changing solutions for our customers.
You will be a key member of a small, energetic Data Science/Machine Learning team. In this role you will drive strategic planning and a cohesive set of technology and machine learning solutions to enable data and platform transformation, by collaborating across all channel teams and the critical technology platforms that support Performance and Customer Experiences. This position provides an opportunity to solve very interesting problems that directly and greatly impact all of our dealer customers. If you have the talent and desire to deliver innovative and intelligent products as well as services at a rapid pace, serving our customers seamlessly through cognitive solutions, this would be the right fit for you!
Who you are
- You have explored the intricacies of a data set to extract insights or have built models that predict or identify patterns used to answer burning business questions
- You have contributed to full stack systems built for speed and distributed computing and feel proud to ship code to delighted end users.
- You yearn to be part of cutting-edge, high profile projects and are motivated by delivering world-class solutions on an aggressive schedule
- You love to learn new technologies, keep abreast of the latest technologies within cloud architecture, and drive your organization to adapt to emerging best practices
- You are the go-to person to answer deep technical questions about which ML algorithm may improve results or what visualization is best to explore relationships in the data
- It would be awesome if you have a robust portfolio on Github or open source contributions you are proud to share
- Regularly engage with business teams to understand their needs, implement prototypes as well as productionalize Machine Learning models
- Combine Data Science and Engineering skills to solve very interesting problems that directly and greatly impact millions of individuals worldwide
- Not only creating ML model prototypes, but also putting them into production in scale
- Challenge the way we do business through application of technology and machine learning solutions to integrate insights in the operational workflow
- Be part of a dynamic team and play a visible role in implementing cutting-edge technology and machine learning solutions with other industry-leading partners
- Work with large, complex data sets to build products and tools that enhance colleague and customer experiences
- Implement highly scalable platform components and tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing, Best Next Action, and Time Series predictions
- Design, code, train, test, deploy and iterate on large scale machine learning systems
- Work with Engineering, Analytics, and Data Science experts to strive for greater functionality in technology ecosystem
- Help craft the direction of machine learning and artificial intelligence at PureCars
Skills & Qualifications
- Bachelor’s degree or higher in Computer Science, Computer Engineering, EE, EEE, Statistics, Math, Industrial Engineering, Operational Research, Physics, Financial Engineering, or related fields.
- Advanced knowledge and 3+ years in one of the following:
- Linear models & descriptive statistics
- Machine Learning
- Deep Learning
- Reinforcement Learning
- Natural Language Processing
- Probabilistic Inference
- Information Retrieval
- Recommendation Systems
- Bayesian Inference
- Advanced time series forecasting
- Strong analytical skills and algorithmic problem solving skills.
- 2+ years of relevant work experience with data science/machine learning
- 3+ years hands-on experience with SQL, and Python/Java
- 3+ years of hands-on experience with machine learning package such as TensorFlow, Keras, ScikitLearn, H20.ai, MXNet, Caffe, Gluon etc.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
- Experience supporting and working with cross-functional teams in a dynamic environment
- At least 2 years of experience working with Machine Learning, Deep Learning or Artificial Intelligence
- At least 2 years of experience programming in Python, Scala or Java
- At least 2 years of experience designing and building full stack solutions utilizing distributed computing or multi-node database paradigms
- Master’s Degree or PhD in Computer Science or Software Engineering or a related field
- At least 2 years of experience with cloud software design using microservices or distributed caching
- A history of publications and conference speaking engagements.
- Open source contributions in the machine learning or data engineering space.
- AWS Certifications
- 3+ years hands-on experience with Advanced SQL, and Python/Java
- 3+ years developing and deploying machine learning solutions in a production environment, and/or produced outstanding research results (Journal and/or Conference publications)
- Expert in one of the machine learning packages such as TensorFlow, Keras, ScikitLearn, H20.ai, MXNet, Caffe, Gluon etc.
- Direct involvement in working with large volumes of data and building, deploying and measuring
- Experience with data pipeline and workflow management tools: Apache NiFi, Informatica, Talend, DataStage, Alteryx, etc. is a plus
- Hands-on experience with GCP, AWS, Hadoop Ecosystem, Spark is a plus.
- Experience with relational SQL and NoSQL databases: Redshift, Snowflake, DynamoDB, Neo4J, MongoDB, Cassandra, DataStaX, etc. is a plus
- Knowledge of / experience with multi/cross/omni-channel CX is a plus