AI/Generative AI Engineer

Role : AI / Generative AI Engineer

Location : Remote ( Pan India ).

Job Type : Full-time or Contract.

Overview :

We are seeking a highly skilled and motivated AI/Generative AI Engineer to join our innovative team.

The ideal candidate will have a strong background in designing, developing, and deploying artificial intelligence and machine learning models, with a specific focus on cutting-edge Generative AI technologies.

This role requires hands-on experience with one or more major cloud platforms (Google Cloud Platform GCP, Amazon Web Services AWS) and/or modern data platforms (Databricks, Snowflake).

You will be instrumental in building and scaling AI solutions that drive business value and transform user experiences.

Key Responsibilities :

Design and Development :

- Design, build, train, and deploy scalable and robust AI/ML models, including traditional machine learning algorithms and advanced Generative AI models (e.g., Large Language Models LLMs, diffusion models).

- Develop and implement algorithms for tasks such as natural language processing (NLP), text generation, image synthesis, speech recognition, and forecasting.

- Work extensively with LLMs, including fine-tuning, prompt engineering, retrieval-augmented generation (RAG), and evaluating their performance.

- Develop and manage data pipelines for data ingestion, preprocessing, feature engineering, and model training, ensuring data quality and integrity.

Platform Expertise :

- Leverage cloud AI/ML services on GCP (e.g., Vertex AI, AutoML, BigQuery ML, Model Garden, Gemini), AWS (e.g., SageMaker, Bedrock, S3), Databricks, and/or Snowflake to build and deploy solutions.

- Architect and implement AI solutions ensuring scalability, reliability, security, and cost-effectiveness on the chosen platform(s).

- Optimize data storage, processing, and model serving components within the cloud or data platform ecosystem.

MLOps and Productionization :

- Implement MLOps best practices for model versioning, continuous integration/continuous deployment (CI/CD), monitoring, and lifecycle management.

- Deploy models into production environments and ensure their performance, scalability, and reliability.

- Monitor and optimize the performance of AI models in production, addressing issues related to accuracy, speed, and resource utilization.

Collaboration and Innovation :

- Collaborate closely with data scientists, software engineers, product managers, and business stakeholders to understand requirements, define solutions, and integrate AI capabilities into applications and workflows.

- Stay current with the latest advancements in AI, Generative AI, machine learning, and relevant cloud/data platform technologies.

- Lead and participate in the ideation and prototyping of new AI applications and systems.

- Ensure AI solutions adhere to ethical standards, responsible AI principles, and regulatory requirements, addressing issues like data privacy, bias, and fairness.

Required Qualifications :

- 3+ years of experience with software development in one or more programming languages, and with data structures/algorithms/Data Architecture.

- 3+ years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

- 3+ years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.

- Proven experience as an AI Engineer, Machine Learning Engineer, or a similar role.

- Strong programming skills in Python.

- Familiarity with other languages like Java, Scala, or R is a plus.

- Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning concepts (e.g., CNNs, RNNs, Transformers), and statistical modeling.

- Hands-on experience with developing and deploying Generative AI models and techniques, including working with Large Language Models (LLMs like GPT, BERT, LLaMA, etc.).

- Proficiency in using common AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, Keras, Hugging Face Transformers, LangChain, etc.

- Demonstrable experience with at least one of the following cloud/data platforms :

1. GCP : Experience with Vertex AI, BigQuery ML, Google Cloud Storage, and other GCP AI/ML services.

2. AWS : Experience with SageMaker, Bedrock, S3, and other AWS AI/ML services.

3. Databricks : Experience building and scaling AI/ML solutions on the Databricks Lakehouse Platform, including MLflow.

4. Snowflake : Experience leveraging Snowflake for data warehousing, data engineering for AI/ML workloads, and Snowpark.

- Experience with data engineering, including data acquisition, cleaning, transformation, and building ETL/ELT pipelines.

- Knowledge of MLOps tools and practices for model deployment, monitoring, and management.

- Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.

- Strong analytical and problem-solving skills.

- Excellent communication and collaboration abilities.