
AI/ML Engineer
1 day ago
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, ).
- Contributions to open-source AI projects or a portfolio showcasing relevant work.
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