Artificial Intelligence Engineer (AI Engineer)

We are seeking a motivated an AI Engineer to join our AI team, focusing on Generative AI (GenAI) and related technologies. The candidate will work closely with cross functional teams, including application development, to design, develop, and deploy end-to-end AI solutions that drive business impact. This role offers an exciting opportunity to contribute to cutting-edge AI projects while growing your technical expertise.

Key Responsibilities

Model Development:

End-to-End Project Ownership:

Testing & Validation:

Collaboration:

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Qualifications

Education:

Experience:

1-4 years of experience in AI/ML development, with exposure to Generative AI, deep learning, NLP, Machine Learning, Computer Vision and Speech technology frameworks. Hands-on experience with end-to-end AI project lifecycles, from data preparation to model deployment.

Experience collaborating with software development teams to integrate AI solutions into applications.

Technical Skills:

Proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, Hugging Face, scikit-learn, llama-index, langchain).

Familiarity with Generative AI techniques (e.g., LLMs, GANs, diffusion models). Proficiency in writing prompts and Fine-tuning LLM

Experience with cloud platforms (e.g., AWS, Azure, GCP) for model training and deployment along with working with Open-source model deployment

Knowledge of software development practices, including version control (Git), CI/CD pipelines, and containerization (Docker).

Understanding of REST APIs, microservices, or web frameworks (e.g., Flask, FastAPI) for application integration.

Basic knowledge of data engineering tools (e.g., SQL, Pandas, Spark) for data preprocessing.

Soft Skills:

Strong problem-solving skills and a proactive approach to tackling challenges. Excellent communication skills to collaborate with technical and non-technical stakeholders. Ability to work in a fast-paced, team-oriented environment.

Nice-to-Have:

Experience with MLOps tools (e.g., MLflow, Kubeflow) for model tracking and deployment.

Role & responsibilities