Senior Machine Learning Engineer, AI Insights

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer, AI Insights in New York (USA).

In this role, you will design and implement advanced machine learning systems that extract actionable insights from massive datasets, shaping the future of intelligent business platforms. You will lead the development of recommendation and ranking systems, transforming structured and unstructured data into high-value outputs. This position offers the opportunity to collaborate with engineers, data scientists, and product teams to scale AI solutions for production environments, while focusing on efficiency, maintainability, and model observability. You will drive impactful ML engineering initiatives that directly influence the performance and capabilities of a high-profile analytics platform. The role emphasizes applied machine learning in a fast-paced environment, combining technical innovation with practical problem-solving.

Accountabilities:

• Own the full machine learning lifecycle, from ideation and feature engineering to model deployment, monitoring, and evaluation.
• Design and implement sophisticated recommendation and ranking systems using techniques such as learn-to-rank, collaborative filtering, and hybrid search.
• Solve complex information retrieval and extraction problems on both structured and unstructured data.
• Collaborate with cross-functional teams, including data engineering, software engineering, and product management, to build robust, scalable ML systems.
• Ensure models are production-ready, maintainable, and observable using best practices for ML operations.
• Drive improvements in AI infrastructure, workflow automation, and model monitoring.

Requirements

• 5+ years of experience in software engineering and/or applied machine learning in production.
• Hands-on experience with recommendation and ranking systems at scale, including LTR algorithms, collaborative filtering, and hybrid search implementations.
• Strong understanding of ML techniques such as clustering, decision forests, and information retrieval.
• Experience serving ML models for batch and streaming inference at scale.
• Proficiency with Python and modern ML frameworks (PyTorch, Scikit-learn, or similar).
• Experience with vector or graph databases (e.g., Milvus, Weaviate, Neo4j).
• Track record of building maintainable, testable, and production-grade ML codebases.
• Familiarity with ML observability tools, A/B testing, and model evaluation pipelines.
• Nice to have: experience with dataset engineering, LLMs, AI orchestration frameworks, text-to-SQL solutions, and CI/CD automation.

Benefits

• Competitive salary range: $106,200 – $210,000 USD, depending on experience and location.
• Comprehensive health benefits including medical, dental, and vision coverage.
• Flexible personal and sick days to support well-being.
• Retirement planning via 401(k) plan.
• Learning and development budget to support ongoing education and professional growth.
• Wellness support including home internet, meals, and fitness reimbursements.
• Virtual team-building activities and social events to strengthen team connection.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

#LI-CL1