AI/ML Engineer

Position Summary :

A rewarding career at HID Global beckons you We are looking for an AI/ML Engineer , who is responsible for designing, developing, and deploying advanced AI/ML solutions to solve complex business challenges.

This role requires expertise in machine learning, deep learning, MLOps, and AI model optimization, with a focus on building scalable, high-performance AI systems.

As an AI/ML Engineer, you will work closely with data engineers, software developers, and business stakeholders to integrate AI-driven insights into real-world applications.

You will be responsible for model development, system architecture, cloud deployment, and ensuring responsible AI adoption.

We are a leading company in the trusted source for innovative HID Global Human Resources products, solutions and services that help millions of customers around the globe create, manage and use secure identities.

Roles & Responsibilities :

- Design, develop, and deploy robust & scalable AI/ML models in Production environments.

- Collaborate with business stakeholders to identify AI/ML opportunities and define measurable success metrics.

- Design and build Retrieval-Augmented Generation (RAG) pipelines integrating vector stores, semantic search, and document parsing for domain-specific knowledge retrieval.

- Integrate Multimodal Conversational AI platforms (MCP) including voice, vision, and text to deliver rich user interactions.

- Drive innovation through PoCs, benchmarking, and experiments with emerging models and architectures.

- Optimize models for performance, latency and scalability.

- Build data pipelines and workflows to support model training and evaluation.

- Conduct research & experimentation on the state-of-the-art techniques (DL, NLP, Time series, CV)

- Partner with MLOps and DevOps teams to implement best practices in model monitoring, version and re-training.

- Lead code reviews, architecture discussions and mentor junior & peer engineers.

- Architect and implement end-to-end AI/ML pipelines, ensuring scalability and efficiency.

- Deploy models in cloud-based (AWS, Azure, GCP) or on-premises environments using tools like Docker, Kubernetes, TensorFlow Serving, or ONNX

- Ensure data integrity, quality, and preprocessing best practices for AI/ML model development.

- Ensure compliance with AI ethics guidelines, data privacy laws (GDPR, CCPA), and corporate AI governance.

- Work closely with data engineers, software developers, and domain experts to integrate AI into existing systems.

- Conduct AI/ML training sessions for internal teams to improve AI literacy within the organization.

- Strong analytical and problem solving mindset.

Technical Requirements :

- Strong expertise in AI/ML engineering and software development.

- Strong experience with RAG architecture, vector databases

- Proficiency in Python and hands-on experience in using ML frameworks (tensorflow, pytorch, scikit-learn, xgboost etc)

- Familiarity with MCPs like Google Dialogflow, Rasa, Amazon Lex, or custom-built agents using LLM orchestration.

- Cloud-based AI/ML experience (AWS Sagemaker, Azure ML, GCP Vertex AI, etc.

- Solid understanding of AI/ML life cycle Data preprocessing, feature engineering, model selection, training, validation and deployment.

- Experience in production grade ML systems (Model serving, APIs, Pipelines)

- Familiarity with Data engineering tools (SPARK, Kafka, Airflow etc)

- Strong knowledge of statistical modeling, NLP, CV, Recommendation systems, Anomaly detection and time series forecasting.

- Hands-on in Software engineering with knowledge of version control, testing & CI/CD

- Hands-on experience in deploying ML models in production using Docker, Kubernetes, TensorFlow Serving, ONNX, and MLflow.

- Experience in MLOps & CI/CD for ML pipelines, including monitoring, retraining, and model drift detection.

- Proficiency in scaling AI solutions in cloud environments (AWS, Azure & GCP).

- Experience in data preprocessing, feature engineering, and dimensionality reduction.

- Exposure to Data privacy, Compliance and Secure ML practices

Education and/or Experience:

- Graduation or masters in computer science or information technology or AI/ML/Data science

- 3+ years of hands-on experience in AI/ML development/deployment and optimization

- Experience in leading AI/ML teams and mentoring junior engineers

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