AI / ML Engineer
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Key skills for this role
About the Role
Datamatics Technologies is seeking an AI/ML Engineer with 3-11 years of experience to design, develop, deploy, and optimize machine learning and generative AI solutions. The role requires hands-on expertise in Python, TensorFlow or PyTorch, and cloud AI platforms like GCP Vertex AI, Azure ML, or AWS SageMaker.
Key Skills for This Role
Responsibilities
- Design, develop, train, and deploy machine learning and deep learning models for enterprise applications
- Build and optimize end to end ML pipelines for data ingestion, model training, evaluation, and deployment
- Develop Generative AI and LLM powered applications using modern AI frameworks
- Collaborate with data engineers, software developers, and business stakeholders to deliver AI driven solutions
- Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security
- Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation
- Implement MLOps best practices including model versioning, monitoring, and CI/CD automation
- Stay current with advancements in AI, machine learning, and cloud AI services
Requirements
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field
- 3–11 years of professional experience in AI, Machine Learning, or Data Science
- Strong proficiency in Python
- Experience developing machine learning solutions using TensorFlow or PyTorch
- Hands on experience with GCP Vertex AI or Azure Machine Learning or AWS SageMaker
- Experience with Azure OpenAI or AWS Bedrock for Generative AI solutions
- Experience with BigQuery ML and Dataflow for data processing and machine learning workflows
- Experience with Hugging Face and LangChain for building LLM powered applications
- Experience with Databricks for data engineering, model development, and analytics workflows
- Experience deploying machine learning models into production
- Strong analytical, mathematical, and problem solving skills
- Excellent communication and collaboration skills
Full Job Posting
Job Overview
- We are seeking a skilled AI / ML Engineer with 3–11 years of experience to design, develop, deploy, and optimize machine learning and generative AI solutions.
- The ideal candidate will have hands on expertise in building scalable AI/ML models, working with cloud native AI platforms, and implementing production ready machine learning pipelines.
- Experience with modern AI frameworks, large language models (LLMs), and MLOps practices is highly desirable.
Key Responsibilities
- Design, develop, train, and deploy machine learning and deep learning models for enterprise applications.
- Build and optimize end to end ML pipelines for data ingestion, model training, evaluation, and deployment.
- Develop Generative AI and LLM powered applications using modern AI frameworks.
- Collaborate with data engineers, software developers, and business stakeholders to deliver AI driven solutions.
- Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security.
- Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation.
- Implement MLOps best practices including model versioning, monitoring, and CI/CD automation.
- Stay current with advancements in AI, machine learning, and cloud AI services.
Required Technical Skills
- Cloud AI Platforms: Hands on experience with GCP Vertex AI or Azure Machine Learning or AWS SageMaker.
- Experience with Azure OpenAI or AWS Bedrock for Generative AI solutions.
- Experience with BigQuery ML and Dataflow for data processing and machine learning workflows.
- Programming & Machine Learning: Strong proficiency in Python.
- Experience developing machine learning solutions using TensorFlow or PyTorch.
- Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts.
- Generative AI & LLM Frameworks: Experience with Hugging Face and LangChain for building LLM powered applications.
- Knowledge of prompt engineering, Retrieval Augmented Generation (RAG), embeddings, and vector databases is preferred.
- Data Engineering & Analytics: Experience with Databricks for data engineering, model development, and analytics workflows.
- Strong understanding of data preprocessing, feature engineering, and large scale data processing.
- MLOps & Deployment: Experience deploying machine learning models into production.
- Knowledge of Docker, Kubernetes, CI/CD pipelines, and model monitoring is an advantage.
Qualifications
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
- 3–11 years of professional experience in AI, Machine Learning, or Data Science.
- Strong analytical, mathematical, and problem solving skills.
- Experience working in Agile development environments.
- Excellent communication and collaboration skills.
Preferred Skills
- Experience with Large Language Models (LLMs) and Generative AI applications.
- Knowledge of Retrieval Augmented Generation (RAG), vector databases, and AI agents.
- Experience with distributed model training and cloud native AI architectures.
- Cloud certifications in AWS, Azure, or Google Cloud are a plus.
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