Machine Learning Engineering

Publicis Groupe ANZ; Birmingham (MI); Remote; USD 87,210 - 119,300; Full time

Benefits offered by this job

Paid Family Care

Tuition Assistance

Flexible working arrangements

‘Work Your World’ Program

Job summary

A leading digital marketing firm in Birmingham is seeking a Machine Learning Engineer to design, build, and maintain scalable ML systems. The ideal candidate will have extensive experience in deploying ML models, collaborating with data teams, and strong proficiency in Python and SQL. The role requires a passion for AI and includes exceptional benefits, competitive compensation, and opportunities for remote work.

Qualifications

• 3-4 years of professional experience in ML engineering or related field.
• 2+ years of hands-on experience deploying ML models.
• Experience in collaborative, cross-functional team environments.

Responsibilities

• Design and build scalable ML pipelines using cloud services.
• Implement CI/CD pipelines for model training and deployment.
• Maintain ML infrastructure and optimize inference performance.

Skills

Python

SQL

MLOps

Data Processing

API Development

Education

Bachelor’s degree in Computer Science

Tools

Vertex AI

Databricks

AWS

Azure

Job description

Company Description

Hi there! We’re Razorfish. We’ve been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What’s different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.

Overview

We’re seeking a Machine Learning Engineer to help design, build, and maintain production-grade ML systems across cloud platforms. This role blends software engineering and ML expertise to translate prototypes into scalable solutions. You’ll own the full ML lifecycle from development and deployment to monitoring and optimization using tools like Databricks, Vertex AI, and other cloud-native platforms. Strong technical skills, collaboration, and a passion for delivering AI at scale are essential.

For this role, we expect the candidate to demonstrate a track record of:

• Collaborating with Data Science teams to deploy ML solutions into production.
• Hands‑on MLOps experience, including model deployment, monitoring, and lifecycle management.
• Designing data warehouses and orchestrating data pipelines to support scalable ML operations.

Responsibilities

ML System Development & Deployment

• Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML).
• Develop and integrate microservices, REST APIs, and webhooks for ML model serving.
• Implement CI/CD pipelines for automated model training, testing, and deployment.
• Create robust data processing workflows for model training and inference.

MLOps & Infrastructure

• Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines).
• Implement model monitoring, versioning, and performance tracking systems.
• Design automated retraining pipelines and manage model lifecycle.
• Ensure reliability, scalability, and security of models in production.
• Optimize inference performance and cost efficiency across cloud platforms.

Software Engineering Excellence

• Write clean, maintainable, and well‑documented code following best practices.
• Implement comprehensive testing strategies including unit, integration, and model testing.
• Contribute to technical design reviews and architecture decisions.
• Maintain high code quality standards and participate in code reviews.

Cross‑Functional Collaboration

• Partner with data scientists to productionize research models and prototypes.
• Collaborate with data engineers to design efficient data pipelines and feature stores.
• Work with product teams to integrate ML capabilities into customer‑facing applications.
• Participate in agile development processes and cross‑functional project planning.
• Provide technical guidance and mentorship to junior team members.

Qualifications

Education & Experience

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field.
• 3‑4 years of professional experience in ML engineering, software engineering, or data science.
• 2+ years of hands‑on experience deploying and maintaining ML models in production.
• Experience working in collaborative, cross‑functional team environments.

Technical Skills

• Programming Languages: Strong proficiency in Python and SQL.
• ML Frameworks: Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras.
• Cloud Platforms: Solid hands‑on experience with GCP, AWS, or Azure.
• ML Platforms: Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks.
• Analytics & Feature Engineering: Proficient with BigQuery, Redshift, Azure Synapse.
• Distributed Processing: Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka.
• Workflow Orchestration: Experience with Airflow, Cloud Composer, Jenkins.
• Networking & Security: Understanding of cloud networking, security, and cost optimization.
• MLOps & DevOps: Familiarity with CI/CD, ML lifecycle management.
• API Development: Experience with REST APIs and microservices.
• Version Control: Proficiency with Git and collaborative development workflows.

Core Competencies

• Strong understanding of ML algorithms, model evaluation, and validation.
• Experience with data preprocessing, feature engineering, and performance tuning.
• Solid software engineering fundamentals and coding best practices.
• Awareness of data privacy, security, and ethical AI principles.
• Excellent collaboration skills with technical and non‑technical stakeholders.
• Self‑driven learner with curiosity about emerging ML technologies.

Preferred Qualifications

Advanced Technical Skills

• MLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines.
• Containerization: Docker; basic Kubernetes knowledge.
• Specialized ML: Exposure to NLP, computer vision, or deep learning.
• Modern ML: Familiarity with LLMs, RAG patterns, transformer architectures.

Professional Experience

• Agile development and cross‑functional collaboration.
• Code review and technical documentation practices.
• Interest in mentorship and knowledge sharing.
• Experience with model validation and software testing principles.

Additional Information

The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best‑in‑class wellness and benefits offerings include:

• Paid Family Care for parents and caregivers for 12 weeks or more.
• Monetary assistance and support for Adoption, Surrogacy and Fertility.
• Monetary assistance and support for pet adoption.
• Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance.
• Tuition Assistance.
• Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more.
• Matching Gifts programs.
• Flexible working arrangements.
• ‘Work Your World’ Program encouraging employees to work from anywhere. Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility).
• Business Resource Groups that support multiple affinities and alliances.

The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents.

Razorfish is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances.

If you require accommodation or assistance with the application or onboarding process specifically, please contact [e-mail].

All your information will be kept confidential according to EEO guidelines.

Compensation Range: $87,210 to $119,300. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third‑party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 9/1/25.

Senior level: Mid‑Senior level
Employment type: Full‑time
Job function: Engineering and Information Technology
Industries: Advertising Services