Machine Learning Engineering Technical Leader

Job Overview

As a Machine Learning Engineering Technical Leader, you will join the Code Generation group at Splunk, a Cisco company, where you will work on automating the code generation process using GenAI techniques. You will be part of a culture that values technical excellence, innovation, and collaboration.

Your Impact

You will own the full lifecycle of research and deployment of next-generation AI systems for intelligent code generation. Your responsibilities will include:

• Defining the scientific roadmap for agentic GenAI, enabling models that not only generate code but reason, plan, self-correct, and integrate with tools and runtime environments.
• Driving efficiency and scalability of distributed training and inference pipelines to balance performance, latency, and cost.
• Collaborating closely with engineering and product to ensure AI breakthroughs translate quickly and safely into high-impact customer capabilities.
• Mentoring and elevating a high-performing research organization, fostering a culture of scientific rigor, creativity, and delivery excellence.
• Shaping long-term AI strategy and innovation, influencing architectural decisions, technical investments, and roadmap direction across the GenAI organization.

Minimum Qualifications

• PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field and 5+ years of post-doctoral or industry experience; or a Master’s degree in a related field and 10+ years of industry experience.
• 3+ years of experience in developing Large Language Models (LLMs) for program synthesis or formal languages.
• 2+ years of experience in Multi-step planning or agentic AI for developer workflows.
• 3+ years of experience with Python and deep learning frameworks such as PyTorch or TensorFlow.
• 3+ years of experience translating research prototypes into production systems, including model deployment, optimization, and evaluation.

Preferred Qualifications

• Strong foundation in experimental design, benchmarking, reproducibility, evaluation metrics, and scientific documentation.
• Experience with training, fine-tuning, or adapting models such as Code-LLaMA, CodeT5, StarCoder, or GPT-based code models for program synthesis, refactoring, unit test generation, static/dynamic analysis, or domain-specific languages (DSLs).
• Background building generative models that target structured languages (e.g., SQL, DSLs, configuration languages, or proprietary query languages/SPL).
• Experience designing agents that plan, call tools/APIs, self-reflect, or drive code to iteratively refine solutions.
• Proven success applying techniques such as chain-of-thought, self-debugging, constrained decoding, or reinforcement learning for software development tasks.
• Experience with distributed training, efficient inference (quantization, LoRA, caching, batching), and cost-aware scaling.
• Familiarity with automated model retraining, dataset curation, synthetic data pipelines, eval harnesses, and model health monitoring.
• Publications in premier AI/ML venues (NeurIPS, ICML, ICLR, ACL, AAAI, KDD, etc.) and/or recognized contributions in the code-gen / LLM community.

Benefits

• Medical, dental, and vision insurance.
• 401(k) plan with a Cisco matching contribution.
• Paid parental leave.
• Short and long-term disability coverage.
• Basic life insurance.
• Paid time away (10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees).
• Flexible vacation time off program.
• 80 hours of sick time off provided on hire date and each January 1st thereafter.
• Optional 10 paid days per full calendar year to volunteer.

Salary Information

The starting salary range posted for this position is $234,400.00 to $296,600.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations.