About Ascendion

Ascendion is a full-service digital engineering solutions company. We make and manage software platforms and products that power growth and deliver captivating experiences to consumers and employees. Our engineering, cloud, data, experience design, and talent solution capabilities accelerate transformation and impact for enterprise clients. Headquartered in New Jersey, our workforce of 6,000+ Ascenders delivers solutions from around the globe. Ascendion is built differently to engineer the next.

Ascendion | Engineering to elevate life

We have a culture built on opportunity, inclusion, and a spirit of partnership. Come, change the world with us:

• Build the coolest tech for world’s leading brands
• Solve complex problems – and learn new skills
• Experience the power of transforming digital engineering for Fortune 500 clients
• Master your craft with leading training programs and hands-on experience

Experience a community of change makers!

Join a culture of high-performing innovators with endless ideas and a passion for tech. Our culture is the fabric of our company, and it is what makes us unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows everyone to be their best at Ascendion.

About the Role:

Job Title: ML Engineer

Role Overview

We are seeking a highly skilled Machine Learning Engineer to support and scale a high-impact ML Decisioning / Recommender Platform used for large-scale digital and email campaign arbitration. The team is expanding its scope to fully own end-to-end ML infrastructure, including software, data, and ML engineering responsibilities.

This role is critical to operating, maintaining, and scaling production-grade ML training pipelines as ownership transitions from a data science team to an engineering-led model.

Key Responsibilities

• Own operations and maintenance of end-to-end ML model training pipelines
• Support and optimize Kubeflow-based ML workflows
• Manage weekly model retraining and release cadence
• Drive cluster optimization, automation, and performance improvements
• Scale ML infrastructure to support significant growth in data volume and new customers
• Support the transition from batch scoring to real-time inferencing
• Reintroduce batch-based scoring to support email arbitration use cases
• Partner with ML engineers, data engineers, and software engineers to ensure platform stability and reliability
• Support CI/CD pipelines, version upgrades, security mandates, and vulnerability remediation
• Assist in transitioning ML pipeline ownership from data science teams
• Ensure scalability and stability during onboarding of new business and customers

Required Skills & Qualifications

Core Skills (Must-Have)

• Strong programming experience in Python (Scala preferred but secondary)
• Solid experience with Kubernetes and containerized ML workloads
• Hands-on experience with ML pipelines, preferably using Kubeflow
• Experience supporting production ML systems end to end

ML & Data Technologies

• ML frameworks: scikit-learn, PyTorch, TensorFlow
• Distributed processing: Spark, Dask
• Hands-on experience training, retraining, evaluating, and supporting models such as Random Forests
• Strong understanding of ML infrastructure, CI/CD, automation, and distributed systems
• Experience with cloud-based ML platforms and large-scale data processing

Nice to Have

• Exposure to Transformer models (aligned with upcoming roadmap)
• Experience working on enterprise-scale ML platforms
• Background in regulated or large-scale environments (preferred, not required)

Location: McLean, VA / New York

Salary Range: The salary for this position is between $109,480 – $128,520 annually. Factors which may affect pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate.

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: [medical insurance] [dental insurance] [vision insurance] [401(k) retirement plan] [long-term disability insurance] [short-term disability insurance] [personal days accrued each calendar year. The Paid time off benefits meet the paid sick and safe time laws that pertains to the City/ State] [12-15 days of paid vacation time] [6-8 weeks of paid parental leave after a year of service] [9 paid holidays and 2 floating holidays per calendar year] [Ascendion Learning Management System] [Tuition Reimbursement Program]

Want to change the world? Let us know.

Tell us about your experiences, education, and ambitions. Bring your knowledge, unique viewpoint, and creativity to the table. Let’s talk!