Lead Machine Learning Engineer – Python (AI Platform)

Key Skills

Database, Docker, Effective communication skills, Git, Github, Google BigQuery, Google Cloud Platform (GCP), Google Dataflow, Keras software library, Kubeflow, Kubernetes-K8s, MongoDB, MySQL, Python Programming, PyTorch, TensorFlow, Terraform

Job Description

UKG is looking to hire a Lead Machine Learning Python Engineer to join our extremely talented Data Science team. As a Lead Machine Learning Python Engineer at UKG, you’ll be embedded on the Data Science team where you can work on the next generation AI Platform. You’ll get to work directly with other Software Engineers, Data Scientists, Machine Learning Engineers, Quality Engineers, Product Managers, and Directors, all of whom make up the team. In this highly collaborative environment, you will have the opportunity to grow as a software engineer and help mentor others.

The Lead Machine Learning Python Engineer will be responsible for developing our machine learning infrastructure and solutions cross functional teams, as well as building AI/ML operation components to help speed up our machine learning development lifecycle. This role will also work together with the entire data science team to support our model building efforts. The ideal candidate is an experienced software engineer in cloud infrastructure and machine learning, ideally GCP and Vertex AI. This Lead Machine Learning Python Engineer role will involve supporting the AI model development process in our AI Pillar

UKG works in an agile environment where there are daily stand-ups, code reviews, and constant communication within each self-managed cross-functional team. The ability to communicate effectively with Product Managers and Architects, as well as work closely with other team members are key components for success in this position.

Primary Responsibilities

• Provide engineering leadership, mentorship, technical direction to small team of other engineers (3-6 members).
• Partner with your Engineering Manager and Architects to ensure engineering tasks understood, broken down and implemented to the highest of quality standards.
• Collaborate with members of the team to solve challenging engineering tasks on time and with high quality.
• Design and develop ML solutions and pipelines applications to support our AI Model and Analytics development on GCP.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Design and implement infrastructure to support the machine learning development lifecycle.
• Work with stakeholders including the Product, Cloud Operations, and Data Science teams
• Create solutions that empower our data scientist team members to rapidly prototype and develop machine learning/analytic solutions.
• Work with data scientists and analytics experts to strive for greater functionality in our machine learning/analytic solutions.
• Take initiative and technical ownership to any project assigned.
• Take an active role in coding design, standards, code reviews, and process improvement.
• Write high-quality code, that is supported by an appropriate level of testing and metrics.
• Work with development teams in an agile context as it relates to software development, including Kanban, automated unit testing, test fixtures, and pair programming.

Qualifications

• 7-10 years engaging and working with cross-functional enterprise level software development projects.
• Proven recent experience as Senior Python Engineer, Java (Spring), or similar role.
• Experience with testing tools such as PyTest, xUnit, mocking frameworks, etc.
• Experience with commonly used data science libraries such as Numpy, Pandas, Scikit-learn, Scipy, and Spacy
• Experience using a deep learning framework such as PyTorch, Tensorflow, or Keras.
• Understanding of machine learning algorithms such as Linear and Logistic regressions, Decision tree, Naive Bayes, KNN, K-means, and Random forest.
• Experience with GCP technologies such as BigQuery, GKE, GCS, DataFlow, Kubeflow, and/or VertexAI
• Experience building and optimizing ML pipelines, preferably in Kubeflow.
• Advanced working SQL knowledge and experience working with relational databases, as well as working familiarity with a variety of databases, preferably BigQuery, MySql, and MongoDB.
• Proficiency with Git as a version control system
• Experience with Docker and Kubernetes
• Familiarity with tools used to automate the deployment of an enterprise software solution to the cloud, Terraform, GitHub Actions, Concourse, Ansible, etc.
• Experience with, or understanding of, Agile/Lean Software Development practices such as Kanban or Scrum.
• Excellent problem solving and communication skills.
• Bachelors or Masters degree in Computer Science, Mathematics, Computational Linguistics or similar field