Shro Systems

We are looking for a highly skilled Generative AI Developer with expertise in Large Language Models (LLMs) to join our AI/ML innovation team.

The ideal candidate will be responsible for building, fine-tuning, deploying, and optimizing generative AI models to solve complex real-world problems.

You will collaborate with data scientists, machine learning engineers, product managers, and software developers to drive forward next-generation AI-powered Responsibilities :

- Design and develop AI-powered applications using large language models (LLMs) such as GPT, LLaMA, Mistral, Claude, or similar.

- Fine-tune pre-trained LLMs for specific tasks (e.g., text summarization, Q&A systems, chatbots, semantic search).

- Build and integrate LLM-based APIs into products and systems.

- Optimize inference performance, latency, and throughput of LLMs for deployment at scale.

- Conduct prompt engineering and design strategies for prompt optimization and output consistency.

- Develop evaluation frameworks to benchmark model quality, response accuracy, safety, and bias.

- Manage training data pipelines and ensure data privacy, compliance, and quality standards.

- Experiment with open-source LLM frameworks and contribute to internal libraries and tools.

- Collaborate with MLOps teams to automate deployment, CI/CD pipelines, and monitoring of LLM solutions.

- Stay up to date with state-of-the-art advancements in generative AI, NLP, and foundation Skills Required Skills :

- LLMs & Transformers: Deep understanding of transformer-based architectures (e.g., GPT, BERT, T5, LLaMA, Falcon).

- Model Training/Fine-Tuning: Hands-on experience with training/fine-tuning large models using libraries such as Hugging Face Transformers, DeepSpeed, LoRA, PEFT.

- Prompt Engineering: Expertise in designing, testing, and refining prompts for specific tasks and outcomes.

- Python: Strong proficiency in Python with experience in ML and NLP libraries.

- Frameworks: Experience with PyTorch, TensorFlow, Hugging Face, LangChain, or similar frameworks.

- MLOps: Familiarity with tools like MLflow, Kubeflow, Airflow, or SageMaker for model lifecycle management.

- Data Handling: Experience with data pipelines, preprocessing, and working with structured and unstructured Desirable Skills :

- Deployment: Knowledge of deploying LLMs on cloud platforms like AWS, GCP, Azure, or edge devices.

- Vector Databases: Experience with FAISS, Pinecone, Weaviate, or ChromaDB for semantic search applications.

- LLM APIs: Experience integrating with APIs like OpenAI, Cohere, Anthropic, Mistral, etc.

- Containerization: Docker, Kubernetes, and cloud-native services for scalable model deployment.

- Security & Ethics: Understanding of LLM security, hallucination handling, and responsible AI :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.

- 2-4 years of experience in ML/NLP roles with at least 12 years specifically focused on generative AI and LLMs.

- Prior experience working in a research or product-driven AI team is a plus.

- Strong communication skills to explain technical concepts and findings Skills :

- Analytical thinker with a passion for solving complex problems.

- Team player who thrives in cross-functional settings.

- Self-driven, curious, and always eager to learn the latest advancements in AI.

- Ability to work independently and deliver high-quality solutions under tight deadlines

(ref:hirist.tech)

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