Responsibilities Assist in building, testing, and maintaining simple automation workflows using n8n. Support integration of APIs and databases into automation tasks and ensure data consistency. Debug and resolve issues in automation pipelines under senior guidance. Document workflow designs, configurations, and maintenance procedures clearly. Work closely with senior developers to implement improvements and optimizations. Contribute to identifying internal opportunities for new automations to improve efficiency. Participate in design reviews and team discussions to share learning and ensure quality standards. Monitor workflow executions and assist in maintaining reliable operations. Skills Must-have 1+ year of experience in workflow automation and system integration. Practical hands-on experience with n8n for designing and maintaining workflows. Good-to-have Familiarity with REST API integrations and basic database connections. Exposure to low-code/no-code tools such as Zapier or Make. Will be a plus Understanding of webhooks and event-driven architectures. Experience with tools like Airtable or Notion for lightweight data handling. Familiarity with version control and collaboration tools such as Git.

Responsibilities Assist in designing and refining prompts for large language models (LLMs) to achieve accurate outputs. Support data labeling, text preprocessing, and data preparation for NLP workflows. Help evaluate prompt performance and suggest improvements based on testing. Contribute to small-scale NLP experiments and proof-of-concept studies. Document prompt variations and results clearly for future reference. Collaborate with senior engineers and data scientists to integrate prompts into applications. Assist in maintaining prompt libraries and managing version control. Participate in team brainstorming sessions for new NLP features or improvements. Skills Must-have 1+ year of experience in natural language processing and prompt engineering focused on LLMs. Hands-on experience in Python, leveraging NLTK or spaCy for text processing. Good-to-have Exposure to OpenAI API or similar LLM services for prompt design and testing. Familiarity with Hugging Face Transformers for basic fine-tuning and experimentation. Will be a plus Understanding of LangChain (basic) and Pinecone for vector-based retrieval tasks. Experience with tools like Streamlit or Gradio for simple NLP demos.

Responsibilities Design and implement scalable machine learning models from data preprocessing to deployment. Lead feature engineering and model optimization to improve performance and accuracy. Build and manage end-to-end ML pipelines using MLOps practices. Deploy, monitor, and maintain models in production environments. Collaborate with data scientists and product teams to understand business requirements and translate them into ML solutions. Conduct advanced data analysis and build visualization dashboards to support insights. Maintain thorough documentation of models, experiments, and workflows. Mentor junior team members on best practices and technical skills. Skills Must-have 2–3 years of experience in machine learning development, focusing on end-to-end model lifecycle. Proficiency in Python with Pandas, NumPy, and Scikit-learn for advanced data handling and feature engineering. Strong hands-on expertise in TensorFlow or PyTorch for deep learning model development. Good-to-have Experience with MLOps tools such as MLflow or Kubeflow for model management and deployment. Familiarity with big data frameworks like Spark or Dask. Exposure to cloud ML services such as AWS SageMaker or GCP AI Platform. Will be a plus Working knowledge of Weights & Biases and DVC for experiment tracking and versioning. Experience using Ray or BentoML for distributed training and model serving.

Responsibilities Design, optimize, and test prompts for LLMs tailored to diverse use cases and client needs. Fine-tune pre-trained language models using custom datasets to achieve high-quality outputs. Lead advanced NLP tasks such as summarization, sentiment analysis, and question answering. Integrate NLP modules and prompt workflows into client or product systems. Develop and maintain robust prompt libraries with version control and documentation. Collaborate with teams to define requirements and translate them into NLP solutions. Monitor and evaluate prompt performance metrics and iterate on improvements. Mentor junior team members on best practices in NLP and prompt engineering. Skills Must-have 2–3 years of experience in NLP and prompt engineering with a focus on large language models. Proficiency in Python with deep expertise in Hugging Face Transformers and OpenAI API. Good-to-have Strong understanding of vector databases such as Pinecone and FAISS. Experience working with LangChain for LLM-based workflows. Will be a plus Knowledge of RAG (Retrieval-Augmented Generation) frameworks and LlamaIndex. Familiarity with cloud AI services such as Vertex AI or Azure OpenAI. Experience with experiment tracking tools like Weights & Biases.