Senior Software Engineer - AI​/ML

Employment Type:

Perm Job Number: 25847 Remote Options:
Remote

Senior Software Engineer – AI/ML

Salary Range: $140,000-$180,000

We are seeking a Senior Software Engineer specializing in AI and Machine Learning to join an innovative AI engineering organization. This role sits at the intersection of applied machine learning, LLM product development, and production-grade software engineering.

The Senior Software Engineer will be responsible for building, training, evaluating, and deploying AI/ML models and agentic systems that power intelligent products and enterprise applications. The ideal candidate combines deep hands-on expertise in PyTorch, transformer architectures, LLMs, and the full machine learning lifecycle with the software engineering discipline required to build reliable, scalable AI solutions in production.

This is an opportunity to play a key role in shaping AI capabilities within a large-scale enterprise environment, working closely with engineering, product, data, architecture, and leadership teams.

• Design, develop, train, fine-tune, and evaluate machine learning models using PyTorch and related libraries.
• Build and maintain ML training pipelines, experiment tracking workflows, and model evaluation frameworks.
• Implement transformer-based models and large language model (LLM) integrations for production use cases, including NLP, information extraction, classification, and generation.
• Apply parameter-efficient fine-tuning techniques such as LoRA, QLoRA, and PEFT to adapt foundation models to domain-specific applications.
• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search pipelines.
• Optimize model inference for latency and throughput through quantization, batching, caching, and other performance techniques.
• Develop and maintain AI evaluation frameworks, including automated evaluations and tests, to ensure model behavior is reliable, safe, and production-ready.

• Design and implement LLM-powered agentic workflows using frameworks such as Lang Chain and Lang Graph.
• Build multi-step reasoning pipelines, tool-calling agents, and autonomous task execution systems that integrate with enterprise data and product APIs.
• Develop prompt engineering strategies, few-shot templates, structured outputs, and validation mechanisms.
• Implement runtime guardrails, failure taxonomies, and quality standards for AI-powered applications.
• Contribute to enterprise AI infrastructure and context-management capabilities that allow AI agents to securely interact with organizational tools, systems, and data.

• Build and maintain MLOps infrastructure supporting model training, experiment tracking, versioning, and deployment.
• Containerize and deploy ML services using Docker and Kubernetes and integrate them with CI/CD pipelines.
• Monitor model performance in production and implement drift detection, feedback loops, and automated retraining processes.
• Ensure AI systems meet organizational security, privacy and compliance requirements, including appropriate data minimization and access controls.
• Partner with data engineering teams to design and maintain feature stores, data pipelines, and training data infrastructure.

• Partner with architecture and AI leadership to define AI architecture patterns, engineering standards, and best practices.
• Collaborate with product managers, UX designers, and software engineers to translate AI capabilities into well-designed product features.
• Conduct code reviews with an emphasis on reproducibility, correctness, maintainability, and production readiness.
• Mentor engineers on AI engineering fundamentals, LLM integration patterns, and responsible AI practices.
• Stay current with the rapidly evolving AI/ML landscape and evaluate emerging models, frameworks, and techniques.
• Contribute to organizational AI maturity initiatives and help establish scalable AI engineering practices.
• Represent AI engineering practices in architecture and technical review forums.

• Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field.
• 6-10+ years of professional software engineering experience
  , including at least 3+ years focused on production ML/AI engineering
  .
• Expert-level proficiency in Python and strong familiarity with the Python ML/AI…