Machine Learning Engineer Search, Recommendations & Personalization

Role: Machine Learning Engineer

Search, Recommendations & Personalization      

Location: Cincinnati, OH (Local Preferred; Open to Strong Remote Candidates)

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Duration: 12-month contract, with a high likelihood of extension/conversion

Requirement Description: 

Position Details:

• Work Authorization: Available on W2 or C2C basis

• Interview Process: 

• Ropes Assessment 

• Internal Screening with Account Executive 

• Technical panel with team

• Feedback Timeline: 24-48 hours after interview

• Start Date: ASAP

Overview:

  Isoft, a large-scale retail and ecommerce organization, is seeking a Senior Machine Learning Engineer to join a team focused on scaling Search, Recommendations, and Personalization platforms that power customer-facing digital experiences.

  This role is ideal for engineers who have successfully deployed machine learning solutions into production and understand how to transform recommendation, ranking, search, and personalization models into highly scalable, enterprise-grade systems. You will work closely with Data Scientists, Product teams, and Engineering partners to build the infrastructure, pipelines, serving layers, and operational systems that support machine learning products at scale.

What You'll Do:

• Design, build, and maintain scalable machine learning infrastructure and data pipelines.

• Deploy, optimize, and support production machine learning systems.

• Build model-serving frameworks that power recommendation, personalization, search, and ranking platforms.

• Partner closely with Data Scientists to productionize machine learning models and features.

• Improve model performance, latency, scalability, reliability, and operational efficiency.

• Develop engineering solutions supporting search, recommendations, personalization, and content discovery initiatives.

• Build and maintain containerized machine learning applications and supporting infrastructure.

• Implement observability, monitoring, and performance optimization strategies.

• Evaluate and support emerging AI technologies, including Agentic AI workflows where appropriate.

• Drive best practices for production machine learning and MLOps across the organization.

Required Qualifications :

• 8+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related disciplines.

• Proven experience deploying recommendation systems, search platforms, ranking engines, or personalization solutions in production environments.

• Strong Python development expertise.

• Experience building machine learning pipelines, model-serving frameworks, and scalable production systems.

• Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).

• Experience with Vertex AI and Vertex Search.

• Experience deploying and managing containerized applications using Kubernetes.

• Experience with model deployment, optimization, monitoring, tuning, and operational support.

• Strong understanding of scaling machine learning solutions from proof-of-concept to enterprise production environments.

• Excellent communication, collaboration, problem-solving, and ownership mindset.

Preferred Qualifications:

• Experience within retail, ecommerce, marketplace, grocery, consumer technology, or similar customer-facing industries.

• Experience with recommendation systems, retrieval systems, search platforms, ranking engines, or personalization technologies.

• Familiarity with LangSmith for AI observability and evaluation.

• Experience with modern AI orchestration frameworks and Agentic AI workflows.

• Experience building and supporting large-scale customer-facing ML platforms.

Technology Stack:

Required Skills

• Python

• Google Cloud Platform (Google Cloud Platform)

• Vertex AI

• Vertex Search

• Kubernetes

• Model Deployment & MLOps

• Recommendation Systems

• Machine Learning Infrastructure

Nice to Have

• LangSmith

• Agentic AI Frameworks

• Search & Ranking Systems

• Personalization Platforms

What Success Looks Like:

Successful candidates will demonstrate:

• Strong ownership, accountability, and initiative.

• The ability to operate effectively in fast-paced and ambiguous environments.

• Resourcefulness in overcoming technical and cross-functional challenges.

• A proactive mindset focused on delivering scalable solutions.

• Strong collaboration across Product, Data Science, and Engineering teams.

• The ability to balance technical excellence with measurable business impact.

Why Join?

You'll play a key role in scaling the machine learning systems behind critical customer-facing experiences, helping deliver smarter search, more relevant recommendations, and highly personalized digital interactions at enterprise scale. This is an opportunity to work with modern ML infrastructure, cloud-native technologies, and emerging AI capabilities while partnering with highly skilled Data Science and Engineering teams.