Senior Machine Learning Engineer

About the job

What You Will Achieve and Key Responsibilities: Research, Design, Develop and Deploy AI models and systems • Lead the research and development of AI models - a varied portfolio ranging from small classifiers to fine-tuning LLM’s for specific use-cases • Design, implement and deploy AI-based solutions to solve business and product problems • Develop and implement strategies to track and improve the performance and efficiency of existing and new AI models and systems • Operationalize efficient dataset creation and management • Execute best practices for end-to-end data and AI pipelines • Work closely with the leadership team on research and development efforts to explore cutting-edge technologies. • Collaborate with cross-functional teams including full-stack engineers, product managers, QA engineers, data annotation experts, SMEs and other stakeholders to ensure successful implementation of AI technologies. Build and Mentor the AI Team: • Work closely with the AI & Engineering Leadership to support hiring of top AI talent. • Uphold our culture of engineering excellence by maintaining high standards in innovation & execution. Why This Matters: Your contributions will be instrumental in advancing Parspec’s AI capabilities, enabling us to build intelligent systems that solve real-world problems in construction technology. By developing scalable AI solutions, you will help digitize an industry while driving innovation through state-of-the-art machine learning techniques. Who You Are: You are a motivated Machine Learning Engineer with at least 5 years of relevant experience who is passionate about working on innovative projects in a dynamic environment. You thrive on solving challenging problems using advanced AI technologies. Minimum Qualifications: • Bachelor’s or Master’s degree in Science or Engineering with strong programming, data science, critical thinking, and analytical skills • 5+ years of experience building in ML and Data science • Recent demonstrable hand-on experience with LLMs - integrating off-the-shelf LLM’s, fine-tuning smaller models, building RAG pipelines, designing agentic flows, and other optimization techniques with LLMs • Strong conceptual understanding of foundational models, transformers, and related research • Strong conceptual understanding of the basics of machine learning and deep learning with expertise in Computer Vision and Natural Language Processing • Recent demonstrable experience with managing large datasets for AI projects. • Experience with implementing AI projects in Python and working knowledge of associated Python libraries - numpy, scipy, pandas, sklearn, matplotlib, nltk, etc. • Experience with Hugging Face, Spacy, BERT, Tensorflow, Torch, OpenRouter, Modal, and similar services/frameworks. • Ability to write clean, efficient, and bug-free code. • Proven ability to lead initiatives from concept to operation while navigating challenges effectively. • Strong analytical and problem-solving skills. • Excellent communication and interpersonal skills Preferred Qualifications: • Recent experience with implementing state-of-the-art scalable AI pipelines for extracting data from unstructured/semi-structured sources and converting it into structured information, along with necessary technical infrastructure to support deployment. • Experience with cloud platforms (AWS, GCP, Azure), containerization (Kubernetes, ECS, etc.), and managed services like Bedrock, SageMaker, etc. • Experience with MLOps practices, e.g. model monitoring, feedback pipelines, CI/CD flows, and governance best-practices • Experience working with applications hosted on AWS or Django web frameworks. • Familiarity with databases and web application architecture. • Experience working with OCR tools or PDF processing libraries. • Completed academic or online specializations in Machine Learning or Deep Learning. • Track record of publishing research in top-tier conferences and journals. • Participation in competitive programming (e.g., Kaggle competitions) or contributions to open-source projects. • Experience working with geographically distributed teams across multiple time zones.

Requirements

• Machine Learning
• Python
• Data Science
• AI models
• Deep Learning

Qualifications

• Bachelor's degree
• Master's degree

Preferred Technologies

• Machine Learning
• Python
• Data Science
• AI models
• Deep Learning