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Generative AI Engineer
7 days ago
JD :
Generative AI Engineer
Experience : 5+ years' experience with AI/ML (2+ years in Gen AI)
Qualifications :
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; Master's or Ph.
- 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 problemsolving 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.
Summary :
We are seeking a skilled General AI Engineer with at least 5 years of experience to join our dynamic team.
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.
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 . E.g. 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.
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