AI/ML Junior Developer

Key Responsibilities:

• Develop and deploy solutions utilizing Large Language Models (LLMs) and Natural Language Processing (NLP) technologies coded in Python.
• Design, implement, and optimize workflows using LangChain, OpenAI APIs

• Work with both GraphDB (e.g., Neo4j, ArangoDB) and VectorDB (e.g., Pinecone, Weaviate) technologies for data storage and retrieval in AI applications.

• Test different AI models (e.g., OpenAI, Claude) to evaluate their performance and ability to succeed at specific tasks, ensuring the best fit for each application.

• Collaborate with team members to integrate AI models into scalable, production-ready applications.
• Provide technical leadership in Generative AI projects, leveraging prior hands-on experience.
• Develop, deploy, and maintain machine learning models and pipelines using Python.
• Design, implement, and optimize traditional ML workflows, ensuring efficiency and scalability.
• Collaborate with data scientists and analysts to preprocess and clean datasets for training and evaluation.
• Conduct experiments with various machine learning algorithms (e.g., decision trees, SVM, neural networks) to identify the best-performing models for specific tasks.
• Integrate ML models into production systems, ensuring robust performance and monitoring.

Requirements:

• 5+ years of experience in Python development. (5 years is just coding not AI. For the Jr it might be less, but for the Sr, we want this.)
• Deep understanding of LLMs and NLP technologies.
• Hands-on experience with LangChain and OpenAI platforms.
• Experience with GraphDB (e.g., Neo4j, ArangoDB) and VectorDB (e.g., Pinecone, Weaviate) for database management.
• Proven experience in Generative AI projects with references or examples.
• Strong understanding of traditional machine learning algorithms and their applications.
• Hands-on experience with frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Proficiency in data manipulation and analysis using libraries like Pandas and NumPy.
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn) for presenting findings.
• Experience with data storage solutions, including relational databases (e.g., PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, Redis).

Bonus Skills:

• Experience with Databricks 

• Familiarity with AutoML tools and techniques.

• Any Certificate related to AI / ML

• Other database technology - Postgres and SqlServer

• NoSQL database experience would be more helpful - Mongo, ElasticSearch

• JSON experience, and development of API's in coding experience
• Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying ML models
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) for model deployment
• Understanding of MLOps practices for managing the ML lifecycle.