AI/ML Engineer

Job Description: AI/ML Engineer
Position Overview: We are looking for a skilled and innovative AI/ML Engineer to join our team. The ideal candidate will have experience in designing, developing, and deploying models, as
well as a strong background in AI/ML and software engineering. You will be responsible for building scalable AI solutions and integrating them into various applications, with a focus on generative AI techniques.

Key Responsibilities:

Design, develop, and deploy machine learning models for a wide range of applications, including classification, regression, clustering, and time series forecasting systems.
Skilled at researching and implementing solutions to address data analytics challenges, leveraging statistics, machine learning, and time series modelling.
Demonstrates a strong understanding of generative AI concepts, coupled with hands-on experience in building robust workflows around Large Language Models (LLMs) using frameworks such as LangChain, LlamaIndex, and similar tools.
Familiarity in designing and implementing Agentic AI workflows, enabling LLMs to autonomously plan, execute, and adapt multi-step tasks by leveraging external tools and systems.
Utilize pre-trained models (e.g., GPT, Llama etc) and fine-tune them for specific applications, such as question answering, summarization, and text generation.
Develop and maintain pipelines for automated model training, validation, and deployment.
Work with cross-functional teams to integrate AI/ML models into production systems, whether on-premises or cloud-based, ensuring seamless operation and scalability.
Document model development processes and create clear, concise reports for stakeholders.

Required Skills:

Strong programming skills in Python, with experience in libraries such as Scikit-learn, Pandas, TensorFlow and PyTorch.
Expertise in machine learning algorithms and statistics.
Extensive experience with generative AI models and frameworks, including working with large pre-trained language models like LLama , mixtral, claude,etc and deploying custom LLMs for specific tasks.
Familiarity with on-premises and cloud platforms for deploying and scaling machine learning models.
Knowledge of MLOps practices, including CI/CD pipelines and containerization.
Proficiency in SQL for data querying, manipulation, and analysis.
Familiarity with version control systems (e.g., Git) and collaborative development workflows

Job Features