Mlops Engineer Undefined

Mlops Engineer

Location :- NYC/Alpharetta GA (Day 1 Onsite)

Must have:

• Strong understanding of AI/ML concepts and techniques.

• Proficiency in programming languages such as Python, with hands on experience in AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

• Experience with AI/ML model lifecycle activities, like data preprocessing, feature engineering, deployment, data visualization, etc.

• Good understanding on model deployment, design, and architecture.

• Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights.

• Familiarity with at least one cloud platforms / hyper-scalers (e.g., Google Cloud Platform, Azure, AWS, NVIDIA) and experience in deploying AI/ML models in cloud environments.

• Experience of integrating AI/ML features into business applications and solutions.

• Experience in implementing and managing ML OpsKnowledge of software development practices, version control systems (e.g., Git), and agile methodologies.

• Excellent communication and collaboration skills to work effectively in cross-functional teams.

• Strong organizational and time management skills, with the ability to prioritize and manage multiple projects simultaneously.

• Experience of 6 to 8 years of relevant experience.

Responsibilities:

• Design and develop AI/ML applications to solve complex business problems.

• Collaborate with data scientists and subject matter experts to understand business requirements and translate them into AI/ML solutions.

• Implement and optimize AI/ML models and create pipelines using programming languages, preferably Python.

• Conduct data preprocessing, feature engineering, and data exploration to ensure the availability of high-quality data for training and evaluation.

• Evaluate and benchmark different AIML models, frameworks, and tools to identify the most suitable solutions for specific use cases.

• Train, validate, and fine-tune AI/ML models using various techniques such as deep learning, reinforcement learning, and natural language processing.

• Deploy AIML models in production environments, ensuring scalability, performance, and reliability.

• Collaborate to integrate AI/ML solutions into existing applications or develop new applications.

• Stay up to date with the latest advancements in AI/ML technologies and industry trends.

• Provide technical guidance and support to junior team members and promote knowledge sharing within the team.

• Flexibility to work as part of a team or an individual contributor.