Senior Associate Machine Learning Engineer

Who you are

• 3+ years experience as a member of a data science, machine learning / AI engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
• 2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries, with experience in shipping production code and models
• 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
• 1+ years of professional experience in building services to host machine learning models in production at scale with cloud computing platforms (e.g. AWS, GCP, etc.)
• 1+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
• Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
• Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
• Professional experience in independently solving ambiguous, open-ended problems and technically leading teams
• Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders
• Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, etc

What the job involves

• Collaborate with a team of innovative engineers to deliver AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making
• Develop relationships with software engineers, machine learning engineers, and data scientists on partner teams
• Apply understanding of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation
• Implement and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
• Work with product, engineering, and data science teams to implement AI-based automation solutions that enhance HR and financial operations
• Collaborate with external AI vendors, cloud providers, and open-source communities to integrate best-in-class technologies into our AI stack
• Contribute to establishing monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time