AI/ML Engineer

AI/ML Engineers code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR).Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. May adapt machine learning to areas such as artificial intelligence, robotics and other products that allow users to have an interactive experience. Work with large scale computing frameworks, data analysis systems. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis, using both general purpose software and statistical languages.

Primary Responsibilities:

• Design, build, test, and maintain scalable AI/ML features and infrastructure, including Virtual Agents, APIs and ML Ops for both generative and non-generative use cases
• Rapidly prototype and deliver high-quality production code using deep AI/ML systems engineering expertise
• Implement and manage cloud infrastructure for AI solutions using Infrastructure as Code
• Troubleshoot and resolve complex issues across development and production
• Contribute across the full software development lifecycle, including design, implementation, testing, CI/CD and operations
• Stay current with AI/ML advancements and introduce innovative tools and techniques
• Mentor junior engineers and collaborate with senior engineers through code reviews and technical discussions
• Analyzes and investigates
• Provides explanations and interpretations within area of expertise
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelors or Masters degree in Computer Science or related field
• 6+ years of professional experience in software engineering, AI/ML engineering, MLOps
• Demonstrated experience deploying AI/ML models into production environments
• AI/ML Expertise
  • Hands-on experience with:
  • Natural Language Processing (NLP), Personalization, Anomaly Detection
  • LLMs and RAG pipelines (e.g., LangChain, LlamaIndex, prompt engineering)
  • ML lifecycle tools (e.g., MLflow)
  • Solid understanding of AI/ML concepts, algorithms, and lifecycle
• Software Engineering Skills
  • Experience with object-oriented programming languages & patterns
  • Proven solid fundamentals in software design, data structures, and algorithms
• Proficiency in:
  • Programming languages: Python, JavaScript/TypeScript, SQL
  • Backend: Node.js, REST APIs
  • Frontend: React.js, Angular, HTML/CSS
  • DevOps/MLOps: Git, Docker, Kubernetes
  • Data Engineering: Databricks, Fabric, ETL pipelines
  • Monitoring: Prometheus, Grafana
• Cloud & Infrastructure
  • Familiarity with microservices architecture and Infrastructure as Code
  • Proven expertise with Azure services, including Azure Active Directory, app services & function apps, AKS, managing and configuring Azure Virtual Networks and NSGs
  • CI/CD and containerization practices
• Collaboration & Communication
  • Proven ability to work cross-functionally with product, design, and engineering teams
  • Proven clear communication of complex AI/ML concepts to technical and non-technical stakeholders
  • Proven curiosity, adaptability and learning agility in ambiguous or evolving environments
  • Proven ownership of outcomes, and a drive to build impactful, scalable solutions
  • Proven commitment to continuous learning and mentoring others

Preferred Qualifications:

• Experience building large-scale, consumer-facing applications
• Experience creating, deploying & Prod support of GenAI Virtual Agents. Copilot Studio experience