Senior AI / MLOps Engineer

We are seeking a highly skilled and motivated Senior AI/ML Engineer/Developer with over 5 years of experience in machine learning, artificial intelligence, and cloud deployment. The ideal candidate should have a strong foundation in developing, training, and deploying AI/ML models, as well as hands-on experience in fine-tuning state-of-the-art models such as LLaMA, GEMMA, and OpenAI models. The candidate must be proficient in deploying models on cloud platforms like Azure and AWS and possess knowledge of best practices in cloud-native AI/ML solutions.

Key Responsibilities:
Model Development and Fine-Tuning:
Design, develop, and fine-tune machine learning models using frameworks such as
TensorFlow, PyTorch, and others.
Experience in working with advanced models like LLaMA, GEMMA, and OpenAI s suite of
models.
Collaborate with data scientists and researchers to improve model accuracy and
performance through iterative tuning.
Cloud Deployment:
Deploy and manage machine learning models in production on cloud platforms such as AWS
(SageMaker, EC2, Lambda) and Azure (Azure ML, AKS).
Ensure scalability, reliability, and eciency of AI/ML applications in the cloud.
Optimize model performance and cost on cloud infrastructures.
Data Management Preprocessing:
Collaborate with data engineers to prepare, clean, and analyze large datasets for training
AI/ML models.
Utilize cloud storage and database services (AWS S3, Azure Blob Storage, RDS) for eective
data management.
AI/ML Model Integration:
Integrate AI/ML models with web applications, APIs, and business workflows.
Collaborate with software engineers for seamless model integration into production
environments.
Continuous Improvement:
Stay updated with the latest developments in AI/ML and cloud technologies.
Implement best practices for machine learning operations (MLOps) including version
control, monitoring, and automation of pipelines.
Participate in peer reviews, research new tools, and contribute to internal knowledge
sharing.

Key Skills and Qualifications:

Education:
Bachelor s degree in Computer Science, Data Science, AI/ML, or a related field (Master s
degree preferred).
Experience:
5+ years of hands-on experience in developing and deploying machine learning models.
Proven experience in fine-tuning models like LLaMA, GEMMA, OpenAI models, or similar.
Strong knowledge of machine learning algorithms, neural networks, NLP, computer vision,
and deep learning techniques.
Experience with model optimization techniques (e.g., hyperparameter tuning, pruning).
Cloud Platforms:
Proficient in deploying AI/ML solutions on cloud platforms (AWS, Azure).
Hands-on experience with services like AWS SageMaker, AWS Bedrock, EC2, Lambda, and
Azure Machine Learning, Azure Kubernetes Service (AKS).
Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for ML workflows.
Programming Languages:
Proficient in Python, C++, or Java for model development.
Experience with libraries such as TensorFlow, PyTorch, Scikit-learn, SparkMlLib or similar.
Familiarity with API development and RESTful services for model deployment.
Soft Skills:
Strong problem-solving skills with the ability to adapt to new technologies.
Excellent communication and collaboration skills.
Ability to work in a fast-paced, innovative environment and contribute to cross-functional
teams.

Preferred Qualification
Experience with MLOps tools and practices (Kubeflow, MLflow, etc.).
Familiarity with large language models (LLMs) and transformers.
Exposure to distributed computing and handling large-scale datasets.
Certifications in AI/ML, and cloud platforms (AWS Certified Machine Learning, Azure AI Engineer,
etc.).