Sr. Machine Learning Engineer

About Fusemachines
Fusemachines is a 10+ years old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.

The Role

We are seeking an experienced Senior Machine Learning Engineer passionate about building impactful products in the search and advertising technology ecosystem. As part of our established AI/ML and Search organization, you will be instrumental in developing and optimizing advanced models to enhance our ultra-low-latency ad-serving platform and consumer-facing search solutions. You will collaborate closely with product, data science, and business teams, significantly contributing to strategic initiatives such as yield optimization, predictive modeling, and improved bidding performance. You will have a clear career progression path and numerous opportunities for both personal and professional growth in an intellectually stimulating and dynamic work environment.

Responsibilities

• Drive end-to-end lifecycle management of AI/ML projects from concept and data acquisition to prototyping, model development, deployment, and ongoing maintenance.
• Implement and champion best practices in MLOps, including data ingestion, model training pipelines, monitoring, alerting, and QA to ensure model reliability and performance.
• Contribute significantly to model architecture decisions, leveraging state-of-the-art machine learning, deep learning, and reinforcement learning techniques.
• Develop and deploy robust feature engineering pipelines and ML services optimized for low latency and high throughput.
• Establish and utilize robust A/B testing and experimentation frameworks to evaluate and iteratively improve model performance.
• Translate research papers into high-quality, production-ready code.
• Communicate effectively, collaborate, and build long-term relationships across the organization.
• Mentor junior team members in achieving engineering excellence and be a change agent on the team.

Basic Qualifications

• Bachelor's with 5-8+ years of industry experience in AI/ML, developing and deploying production-level ML systems.
• Proven expertise in building AI/ML models in at least one of the following domains: Ads, relevance, ranking, recommendation systems, and search.
• Breadth and depth knowledge of statistical learning, machine learning, and deep learning.
• Experience in building distributed, low-latency, high-throughput batch and online ML services.
• Hands-on experience in deploying and maintaining ML pipelines in production, including feature engineering and model monitoring frameworks.
• Fluency in Python and proficiency with distributed frameworks (Spark, Hadoop), SQL, and cloud infrastructure.
• Experience with ML packages such as Tensorflow or PyTorch, scikit-learn, and Spark ML.
• Ability to operate efficiently in a high-paced, multi-functional, and rapidly evolving environment.

Preferred Qualifications

• 2+ years of experience in building ML models in the ads space or recommender systems.
• Experience in building CTR/CVR prediction, ad selection, keyword bidding, and Learning to Rank models.
• Experience in building and deploying online experimentation frameworks to identify right models and features at scale.
• Experience in building ad selection frameworks using reinforcement learning or contextual bandits.
• Experience in fine tuning LLMs or building them from scratch.
• Experience in building products using Generative AI powered autonomous agents.