Manager, Data Engineering

Machine Learning Engineer

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: 1. Collaborating with Data Science teams to deploy ML solutions into production. 2. Hands-on MLOps experience, including model deployment, monitoring, and lifecycle management. 3. 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 (2+ years)
• 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 View email address on click.appcast.io.

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