Sr. Machine Learning Engineer

• Lead the end-to-end development of machine learning solutions, including problem framing, data acquisition, solution architecture, model development, testing, and deployment.
• Train/Fine-tune generative AI models using state-of-the-art training techniques such as LoRA/QLoRA
• Leverage GenAI for cutting edge solutions including RAG (enterprise), agentic workflows, image/video gen, wrapper apps etc. using APIs, orchestration frameworks, observability and evaluation libraries
• Train/Fine-tune and optimize state-of-the-art computer vision models for image recognition, object detection, segmentation, and similar tasks.
• Develop and implement advanced data scraping and web crawling pipelines to collect and preprocess large-scale datasets
• Implement appropriate ML/DL models and algorithms to address business-specific challenges
• Collaborate with cross-functional teams, including clients, product managers, and domain experts, to define project goals and requirements.
• Stay updated with the latest trends and breakthroughs in AI/ML and integrate relevant advancements into the development process.
• Manage deployment pipelines, ensuring seamless integration of ML models with production systems.
• Drive performance optimization for models and systems, including hyperparameter tuning and retraining strategies.
• Mentor junior engineers and provide technical leadership to elevate the overall team capability.

• Education: Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related fields.
• Experience:

• Minimum 4 years of professional experience in machine learning/AI
• Proven expertise in handling end-to-end ML project lifecycles, from data processing to production deployment.
• Technical Skills:

• Proficient in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, OpenCV etc. and API development using Flask, FastAPI etc.
• Expertise in LangChain, Pinecone, OpenAI Functions, FAISS, and other tools for building RAG-based systems and mainstream agentic workflows for dynamic automation and contextual retrieval
• Strong experience with deep learning architectures (CNNs, RNNs, Transformers, GANs).
• Hands-on experience with large-scale model training and fine-tuning on cloud platforms (AWS, GCP, Azure).
• Solid knowledge of data preprocessing, augmentation, and feature engineering techniques.
• Familiarity with MLOps tools for model versioning, monitoring, and deployment (e.g., MLflow, Docker, Kubernetes).
• Soft Skills:

• Strong problem-solving skills with an analytical mindset.
• Excellent communication and ability to work collaboratively in a team environment.
• Leadership qualities to guide and mentor team members effectively.

• Work on cutting-edge projects that push the boundaries of AI and ML
• Build AI solutions that solve real-world problems and help businesses become efficient and grow
• Collaborate with a team passionate about innovation and growth
• Access to the latest tools, technologies, and resources for professional development
• Be part of a global team and a supportive work environment that values diversity, creativity, and technical excellence

The Plum Tree Group