Sr. Machine Learning Engineer

At Enable, we are transforming the supply chain with our cutting-edge rebate management software. We see rebates as a strategic advantage, strengthening partnerships, driving smarter decisions, and unlocking significant value across the entire supply chain – from manufacturers to consumers.

After securing $276M in Series A-D funding, we are positioned for continued, significant growth. Since the launch of our flagship product in 2016, we have been rapidly scaling our client base, product offerings, and built a team of top-tier talent committed to reshaping the industry.

We’re hiring aSenior Machine Learning Engineerto join our AI and Architecture team, contributing to the design, development, and deployment of cutting-edge machine learning systems. In this role, you’ll work closely with ML scientists, data engineers, and product teams to help bring innovative solutions—such asretrieval-augmented generation (RAG)systems,multi-agent architectures, andAI agent workflows—into production.

As a Senior Machine Learning Engineer, you’ll play a key role in developing and integrating cutting-edge AI solutions—includingLLMs and AI agents—into our products and operations at a leading SaaS company. You’ll collaborate closely with product and engineering teams to deliver innovative, high-impact systems that push the boundaries of AI in rebate management. This is a highly collaborative and fast-moving environment where your contributions will directly shape both the future of our platform and your own growth.

Key Responsibilities

• Design, build, and deployRAG systems, including multi-agent and AI agent-based architectures for production use cases.
• Contribute to model development processes includingfine-tuning, parameter-efficient training (e.g., LoRA, PEFT), and distillation.
• Build evaluation pipelines tobenchmark LLM performanceand continuously monitor production accuracy and relevance.
• Work across the ML stack—from data preparation and model training to serving and observability—either independently or in collaboration with other specialists.
• Optimize model pipelines forlatency, scalability, and cost-efficiency, and support real-time and batch inference needs.
• Collaborate with MLOps, DevOps, and data engineering teams to ensure reliable model deployment and system integration.
• Stay informed on current research and emerging tools inLLMs, generative AI, and autonomous agents, and evaluate their practical applicability.
• Participate in roadmap planning, design reviews, and documentation to ensure robust and maintainable systems.

Required Qualifications

• 5+ years of experiencein machine learning engineering, applied AI, or related fields.
• Bachelor’s or Master’s degree inComputer Science, Machine Learning, Engineering, or a related technical discipline.
• Strong foundation inmachine learning and data science fundamentals—including supervised/unsupervised learning, evaluation metrics, data preprocessing, and feature engineering.
• Proven experience building and deployingRAG systemsand/orLLM-powered applicationsin production environments.
• Proficiency inPythonand ML libraries such asPyTorch, Hugging Face Transformers, or TensorFlow.
• Experience withvector searchtools (e.g., FAISS, Pinecone, Weaviate) andretrieval frameworks(e.g., LangChain, LlamaIndex).
• Hands-on experience withfine-tuning and distillationof large language models.
• Comfortable withcloud platforms(Azure preferred), CI/CD tools, and containerization (Docker, Kubernetes).
• Experience withmonitoring and maintaining ML systemsin production, using tools like MLflow, Weights & Biases, or similar.
• Strong communication skills and ability to work across disciplines with ML scientists, engineers, and stakeholders.

Preferred Qualifications

• PhD inComputer Science, Machine Learning, Engineering, or a related technical discipline.
• Experience withmulti-agent RAG systemsor AI agents coordinating workflows for advanced information retrieval.
• Familiarity withprompt engineeringand building evaluation pipelines for generative models.
• Exposure toSnowflakeor similar cloud data platforms.
• Broader data science experience, including forecasting, recommendation systems, or optimization models.
• Experience withstreaming data pipelines,real-time inference, and distributed ML infrastructure.
• Contributions toopen-source ML projectsor research in applied AI/LLMs.
• Certifications inAzure, AWS, or GCPrelated to ML or data engineering.

Total Rewards:

At Enable, we’re committed to helping all Enablees grow. During the interview process, we assess your level based on experience, expertise, and role scope, aligning it with our compensation bands. Starting pay is determined by factors like location, skills, experience, market conditions, and internal parity.

Salary/TCC is just one component of Enable’s total rewards package. Enable is committed to investing in the holistic health and wellbeing of all Enablees and their families. Our benefits and perks include, but are not limited to:

Paid Time Off:Ample days off + 8 bank holidays
Wellness Benefit:Quarterly incentive dedicated to improving your health and well-being
Private Health Insurance:Health and life coverage for you and your family
Electric Vehicle Scheme:Drive green with our EV program
Lucrative Bonus Plan:Enjoy a rewarding bonus structure subject to company or individual performance
Equity Program:Benefit from our equity program with additional options tied to tenure and performance
Career Growth:Explore new opportunities with our internal mobility program
Additional Perks:

Training:Access a range of workshops and courses designed to boost your professional growth and take your career to new heights.

According to LinkedIns Gender Insights Report, women apply for 20% fewer jobs than men, despite similar job search behaviors. At Enable, we’re committed to closing this gap by encouraging women and underrepresented groups to apply, even if they don’t meet all qualifications.

Enable is an equal opportunity employer, fostering an inclusive, accessible workplace that values diversity. We provide fair, discrimination-free employment, ensuring a harassment-free environment with equitable treatment.

We welcome applications from all backgrounds. If you need reasonable adjustments during recruitment or in the role, please let us know.

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