AI/ML Developer

Job Title: AI Engineer
Role Overview:
We are seeking a talented and experienced Artificial Intelligence Engineer to design, develop, and train advanced AI and machine learning models. You will be a key member of our data science team, responsible for the research, design, and implementation of cutting-edge models, with a specific focus on private AI and Generative AI solutions. This role is for a hands-on developer who is passionate about building intelligent systems from the ground up.
Key Responsibilities:
Model Research & Development:Participate in the research, design, and implementation of AI/ML solutions. This includes selecting appropriate algorithms, defining model architectures (e.g., RAG, agents), and exploring new training datasets.
Data and Feature Engineering:Clean, prepare, and transform large, complex datasets for model training. Define and implement feature engineering and data preprocessing pipelines to optimize model performance.
Model Training & Optimization:Train and fine-tune machine learning and deep learning models. Analyze model errors and performance metrics and design strategies to overcome them through hyperparameter tuning and model architecture improvements.
Prototype & Experimentation:Build AI models from scratch and develop proofs-of-concept to demonstrate the potential and limitations of AI for new products.
Collaboration: Work closely with product managers and business stakeholders to understand business problems and define the scope of AI solutions. Collaborate with MLOps Engineers to ensure seamless transition of models to production.
Required Qualifications:
Experience: 3-5+ years of experience in an AI/ML or data science role, with a proven track record of developing and experimenting with AI models.
Technical Skills:
o Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, and Hugging Face.
o Solid understanding of machine learning algorithms, deep learning, and advanced AI concepts, including RAG architectures and LLMs.
o Experience with data manipulation and analysis using libraries like Pandas and tools like SQL.
o Familiarity with vector databases (e.g., Pinecone, FAISS) and context engineering.
Soft Skills:
o Strong problem-solving and critical thinking skills.
o Excellent communication skills with the ability to explain complex technical concepts.