Gen AI

Exp required: 5+ years experience with AI/ML (2+ years in Gen AI)    

Job Description:

We are seeking a skilled General AI Engineer with at least 5 years of experience to join our dynamic team. The ideal candidate will have a strong background in artificial intelligence, machine learning, and deep learning techniques.  As a general AI engineer, you will play a crucial role in developing, implementing, and maintaining advanced AI systems that drive innovation and solve complex problems. You will collaborate with cross-functional teams to design and deploy AI solutions that enhance products and services, leveraging your expertise to push the boundaries of what AI can achieve.

Skills and Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field; Master’s or Ph.D.         
• Proficiency in programming languages such as Python (preferred) or R.
• Strong understanding of neural networks, deep learning frameworks (TensorFlow, PyTorch), and other AI techniques.         
• Excellent problem-solving skills and ability to think critically about complex technical challenges.         
• Should have experience in accessing Hugging Face, TensorFlow Hub, Kaggle sites.         
• Experience with natural language processing (NLP), computer vision, or reinforcement learning is a plus.         
• Proven track record of delivering successful AI projects from conception to deployment.    

Roles and Responsibilities: 

• Develop and implement cutting-edge AI algorithms and models to solve complex problems. 
• Design, build, and deploy scalable AI systems that deliver value to the organization.
• Collaborate with cross-functional teams to gather requirements and understand business needs.
• Conduct research to stay up-to-date with the latest advancements in AI and machine learning.
• Optimize AI models for performance, scalability, and efficiency. 
• Provide technical guidance and mentorship to junior team members. 
• Work closely with product managers and stakeholders to define project goals and milestones. 
• Evaluate and select appropriate tools and technologies for AI development and deployment. 
• Participate in code reviews, testing, and debugging to ensure high-quality AI solutions.
• Stay informed about industry best practices and emerging trends in AI and machine learning. 
• Communicate complex technical concepts to non-technical stakeholders.

Must-have skill sets: 

• Expertise in Python, Data Structures, and API Calls- Solid foundation for working with generative AI models and frameworks.         
• Strong Communication Skills (Documentation & Presentations)- Ability to clearly document/present complex technical concepts for both technical and non-technical audiences.         
• Effective Teamwork and Solo Work- Collaborate effectively on large projects while also possessing the ability to independently drive research and development efforts.         
• Data Mining and Text Processing- Extract valuable insights from various data sources to train and improve generative models.         
• Building RAG Pipelines (Highly Desired) – Demonstrated experience building retrieval-augmented generation pipelines, a key technique in generative AI.         
• Machine Learning (ML), Natural Language Processing (NLP), Generative Adversarial Networks (GANs), Transformers & BERT flavors, Hugging Face Model Implementation and Fine-Tuning:         
• Solid understanding of these core concepts for generative AI development. 
• Hands-on Experience with Vector Databases: Experience with Chroma DB, PineCone, Milvus, FAISS, Arango DB for data storage and retrieval relevant to generative AI projects. 
• Collaboration- Ability to collaborate effectively with Business Analysts (BAs), Development Teams, and DevOps teams to bring generative AI solutions to life.
• Hands-on Experience of Embedded Models: Familiarity with deploying generative models on resource-constrained devices can be a significant asset.
• Ex: Open AI – Ada Embedding 002 model         
• Experience with POC Tools (Streamlit, Gradio) – Ability to rapidly prototype and showcase generative AI concepts.
• Cloud Experience (AWS Bedrock or similar)-Expertise in managing and deploying large-scale generative AI models on cloud platforms with basic knowledge such as EC2, ECS, ECR, S3, Sagemaker etc.
• Expertise in Specific LLMs (Any one deep knowledge in OpenAI, Jurassic-1 Jumbo, LLAMA, mistral, Mixtral, Gemma, Gemini Pro) – In-depth knowledge of a particular LLM may be required depending on the specific project focus.