Machine Learning Engineer

About The Company

Evlo AI is a pioneering technology company dedicated to transforming enterprise solutions through innovative artificial intelligence and machine learning technologies. Our mission is to empower organizations by delivering intelligent, scalable, and reliable AI-driven systems that enhance operational efficiency and decision-making processes. With a focus on cutting-edge research and practical application, Evlo AI strives to stay at the forefront of the AI industry, fostering a collaborative environment where talent and innovation thrive.

About The Role

The role owns the end-to-end design, implementation, and scaling of machine learning systems powering high-throughput enterprise applications. The team works at the intersection of applied research and platform engineering, building resilient infrastructure that ensures models operate reliably at production scale. This position offers an exciting opportunity to work on complex, large-scale systems, contributing to the development of innovative solutions that have a significant impact on our clients' businesses. The ideal candidate will be passionate about deploying scalable ML models, optimizing infrastructure, and collaborating across teams to deliver high-quality AI products.

Qualifications

• 3 to 6 years of professional experience in machine learning engineering or applied software development.
• Strong proficiency in Python, with hands-on experience using modern deep learning frameworks such as PyTorch or TensorFlow.
• Proven track record of deploying and maintaining machine learning models in production environments on cloud platforms like AWS or GCP.
• Solid understanding of software engineering principles, including CI/CD pipelines and microservices architecture.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related technical field.
• Bonus: Experience with large language model (LLM) orchestration frameworks, vector databases, or large-scale distributed computing systems.

Responsibilities

• Architect and deploy production-grade machine learning models utilizing Python, PyTorch, and cloud infrastructure on AWS to meet enterprise needs.
• Build and maintain robust data ingestion and feature engineering pipelines using Apache Spark and SQL, supporting continuous model training and updates.
• Optimize model serving architectures for low latency and high availability, leveraging containerization tools such as Docker and Kubernetes to ensure seamless deployment and scaling.
• Implement comprehensive monitoring systems to track data drift, concept drift, and system performance regressions in real time, ensuring model reliability and accuracy.
• Collaborate closely with backend engineers and product teams to integrate machine learning capabilities seamlessly into core software services, enhancing product functionalities.
• Participate in internal engineering standards by writing clean, well-tested code, and engaging in rigorous peer code reviews to uphold quality and maintainability.

Benefits

At Evlo AI, we believe in supporting our employees both professionally and personally. We offer competitive compensation packages, comprehensive health insurance, and flexible work arrangements to promote work-life balance. Employees have access to ongoing learning and development opportunities, including technical training and conference participation. Our collaborative and innovative environment encourages continuous growth, with opportunities to work on cutting-edge projects that make a real difference in the industry. Additionally, we provide a vibrant company culture that values diversity, inclusion, and mutual respect, fostering a workplace where everyone can thrive.

Equal Opportunity

Evlo AI is an equal opportunity employer committed to creating a diverse and inclusive workplace. We do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, or any other protected status. We believe that a diverse team fosters innovation and creativity, and we are dedicated to providing an equitable environment for all employees to succeed and grow.