AI Engineer

Job Description :

Role & Responsibilities :

- Model Development : Design, develop, and fine-tune Generative AI models (e.g., LLMs, GANs, VAEs) for applications such as text generation, image and video analysis and insight generation.

- End-to-End Project Ownership : Collaborate with stakeholders to define project requirements, develop AI pipelines, and deploy models into production environments.

- Application Integration : Work closely with application development teams to integrate AI models into web, mobile, or enterprise applications, ensuring seamless functionality.

- Data Processing : Preprocess and analyze large datasets to prepare them for model training, including data cleaning, feature engineering, and augmentation.

- Testing & Validation : Conduct rigorous testing, validation, and monitoring of AI models to ensure accuracy, robustness, and reliability in production.

- Collaboration : Partner with product managers, software engineers, and data scientists to align AI solutions with business objectives and technical requirements.

- Stay Updated : Keep abreast of the latest advancements in GenAI, machine learning, and related fields to propose innovative solutions.

Qualifications :

Education : Bachelors degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Masters degree is a plus.

Experience :

- 2- 6 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.

- Familiarity with front-end or back-end development (e.g., JavaScript, React, Node.js).

- Contributions to open-source AI projects or a portfolio showcasing relevant work.