About Fusemachines
Role
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
Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.
