AI/ML Engineer

Summary

Join Luminexis.AI, a company building human-centered AI systems, as an AI/ML Engineer. You will design, build, and deploy enterprise-grade AI solutions, translating business requirements into scalable systems. This role demands 6-8 years of hands-on machine learning and AI development experience. You will lead technical implementation across diverse client environments and drive innovation in AI service offerings. The ideal candidate will collaborate with various teams, ensuring security and compliance in AI implementations. You will also mentor junior engineers and contribute to technical architecture reviews.

Requirements

• 6-8 years of hands-on experience in machine learning and AI development
• Strong Proficiency in Python with deep knowledge of ML frameworks such as TensorFlow, PyTorch, scikit-learn
• Strong experience with cloud ML platforms (Azure ML, AWS SageMaker, Google AI Platform)
• Expertise in data processing tools (Spark, Pandas, SQL) and big data technologies
• Experience with containerization (Docker, Kubernetes) and MLOps tools (MLflow, Kubeflow, DVC)
• Deep understanding of machine learning algorithms, statistics, and mathematical foundations
• Experience with deep learning architectures (CNNs, RNNs, Transformers, GANs)
• Knowledge of NLP techniques, computer vision, and time series forecasting
• Understanding of model explainability, bias detection, and ethical AI principles
• Experience with A/B testing, experimentation design, and statistical analysis
• Strong software development skills with experience in agile methodologies
• Knowledge of system design patterns and distributed computing principles
• Experience with API development, microservices architecture, and database design
• Familiarity with DevOps practices and infrastructure as code
• Understanding of data security, privacy regulations, and compliance requirements
• Ability to communicate complex technical concepts to non-technical stakeholders
• Experience working in cross-functional teams with business analysts and project managers
• Proven track record of delivering production-ready AI solutions in enterprise environments
• Bachelor's or Master's degree in Computer Science, Data Science, or related field
• Successfully deliver 2-3 concurrent AI/ML projects with 99%+ uptime in production
• Achieve model performance metrics that exceed baseline requirements by 15-20%
• Implement scalable solutions that handle 10x traffic growth without performance degradation
• Maintain code quality standards with 90%+ test coverage and zero critical security vulnerabilities
• Drive measurable business outcomes through AI implementations with documented ROI improvements
• Contribute to 2-3 new AI service offerings or accelerators annually
• Receive positive client feedback on technical expertise and solution quality
• Build reusable frameworks and components that reduce project delivery time by 25%
• Mentor 2-3 junior engineers with demonstrated skill development and career progression
• Establish technical best practices and standards adopted across the engineering team

Responsibilities

• Design & Develop AI/ML Solutions
• Architect and build end-to-end machine learning pipelines from data ingestion to model deployment
• Develop custom AI models including supervised, unsupervised, and deep learning algorithms
• Implement natural language processing, computer vision, and predictive analytics solutions
• Design scalable MLOps frameworks for model versioning, monitoring, and automated retraining
• Optimize model performance for production environments with focus on latency and accuracy
• Lead Technical Implementation & Integration
• Collaborate with product managers, business analysts to translate functional requirements into technical specifications
• Develop capabilities to integrate AI/ML solutions with existing enterprise systems (CRM, databases, APIs, etc.)
• Develop RESTful APIs and microservices for AI model serving and consumption
• Implement real-time and batch inference systems using cloud platforms (Azure, AWS, GCP)
• Ensure security, compliance, and data governance standards in AI implementations
• Drive Data Engineering & Model Operations
• Build robust data preprocessing and feature engineering pipelines
• Implement automated model training, validation, and deployment workflows
• Design monitoring systems for model drift detection and performance tracking
• Establish CI/CD pipelines for machine learning model lifecycle management
• Optimize data storage and retrieval systems for large-scale AI workloads
• Provide Technical Leadership & Innovation
• Mentor junior engineers and guide technical decision-making across projects
• Research and evaluate emerging AI technologies and frameworks
• Lead proof-of-concept development for new AI service offerings
• Contribute to technical architecture reviews and solution design sessions
• Support pre-sales activities with technical expertise and solution demonstrations