Summary
✨ AI‑Generated
Seeking an AI and machine learning engineer to design, develop, and deploy intelligent models powering modern productivity solutions. The role involves building scalable AI systems and improving automated workflows.
Highlights
Work on AI-driven solutions with a focus on innovation, automation, and scalable intelligent systems.
Description
Company Description:
Birbal AI builds AI-driven tools that help businesses and individuals work smarter, increase productivity, and accelerate innovation.
The company focuses on transforming everyday workflows by automating routine tasks and enabling users to focus on high-impact goals.
Its solutions are scalable and adaptable, designed to meet diverse industry needs and support both startups and large enterprises.
Birbal AI emphasizes creativity, efficiency, and continuous improvement, offering technology that evolves alongside its customers’ ambitions.
Team members join a mission-driven environment committed to empowering smarter decisions and unlocking new possibilities.
Role Description:
As an Artificial Intelligence & Machine Learning Engineer at Birbal AI, you will design, develop, and deploy machine learning and AI models that power next-generation productivity and innovation tools.
This full-time hybrid role is based in Fort George G.
Meade, MD, with flexibility for partial work from home.
On a day-to-day basis, you will analyze complex datasets, implement algorithms and neural network architectures, and build end-to-end ML pipelines from data ingestion to model monitoring.
You will collaborate with cross-functional teams to translate product requirements into technical solutions, optimize model performance, and ensure scalable, secure, and maintainable code.
You will also participate in code reviews, experiment tracking, documentation, and continuous improvement of the AI platform.
Qualifications:
Strong foundation in Computer Science and Algorithms, with the ability to design and implement efficient, scalable solutions.Proficiency in Pattern Recognition and Neural Networks for building and refining ML models that address real-world problems.Solid understanding of Statistics to support experimental design, model evaluation, and data-driven decision-making.Experience with programming languages commonly used in ML (such as Python), and frameworks like TensorFlow, PyTorch, or similar.Hands-on experience with data preprocessing, feature engineering, and building end-to-end ML pipelines in production environments.Knowledge of cloud platforms and MLOps practices for deploying, monitoring, and scaling AI solutions.Effective communication and collaboration skills, with the ability to work on hybrid teams and explain technical concepts to non-technical stakeholders.Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience.Experience in applied AI for productivity tools, workflow automation, or enterprise software is a plus.
