- Take prototypes developed by the ML modeling team and drive them into production, ensuring smooth deployment and management of ML models on cloud at scale.
- Collaborate with DevOps engineers to effectively manage cloud compute resources for ML model deployment, monitoring, and performance optimization.
- Monitor real-time performance of deployed models, analyze performance data, and proactively identify and address performance issues to ensure optimal model performance.
- Work in a highly collaborative and diverse team environment, actively contributing to team goals, participating in fast iteration cycles, and adapting to evolving project requirements.
- Collaborate with ML scientists, software engineers, data engineers and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, and automated model deployment.
- Stay up-to-date with the latest advancements in MLOps technologies and best practices, and provide expertise in recommending and implementing new tools and techniques to improve the efficiency and effectiveness of ML model deployment and management processes.
- Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability in a timely and efficient manner.
Participate in the development of documentation, standard operating procedures, and guidelines related to MLOps processes, tools, and best practices. - Contribute to the continuous improvement of the team's processes and workflows, and share knowledge and expertise with team members to promote a collaborative learning environment.
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- Minimum of 2 years of hands-on experience in MLOps, deploying and managing machine learning models in production environments, preferably in cloud-based environments.
- Strong experience with tools and technologies such as Git, Docker, Kubernetes, Jenkins, CI/CD pipelines, monitoring and logging frameworks, and cloud platforms (e.g., AWS, GCP, Azure).
- Solid understanding of machine learning concepts and workflows, and familiarity with popular machine learning frameworks and libraries (e.g., TensorFlow, PyTorch) (e.g., scikit-learn).
- Experience with deployment and management of natural language processing (NLP) models, question answering (QA) systems, or chatbot applications is highly desirable.
- Strong problem-solving and analytical skills, with the ability to troubleshoot and resolve complex technical issues related to ML model deployment and performance.
- Excellent teamwork and collaboration skills, with the ability to work effectively in cross-functional teams, adapt to fast iteration cycles, and contribute to team goals.
- Strong communication skills, with the ability to communicate complex technical concepts to both technical and non-technical stakeholders.
Demonstrated ability to learn and adapt to new technologies, tools, and best practices in MLOps. - Proven ability to work in a fast-paced, dynamic, and innovative environment, with a strong sense of ownership and accountability for delivering high-quality results.
Lead MLOps Engineer - Boston, United States - Unify
Description
Why Unify AI:
Do you want to be a part of a profitable AI startup with a leadership team that has a track record of successful IPOs? Do you want to build an AI driven reasoning system that revolutionizes customer experience? Do you actually want to see your ideas, your architecture and innovations really impact the business? If so, Unify is hiring
What you'll do:
We are seeking a highly skilled and motivated Lead MLOps Engineer to join our dynamic team at Unify AI. The successful candidate will play a foundational role in the development, deployment, and management of intelligent reasoning systems and question answering chatbot models on vectorized knowledge bases for enterprise contact centers.
Responsibilities:
Requirements:
If you are a highly skilled and motivated MLOps Engineer with a passion for deploying and managing ML models at scale, and thrive in a collaborative and fast-paced environment, we would love to hear from you Join us in our mission to develop cutting-edge AI solutions for enterprise contact centers and make a meaningful impact on the way businesses interact with their customers.
Unify strives to be a place to which people can bring the ultimate expression of themselves and their potential—starting with our hiring process. We do not discriminate based on race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation. We foster an inclusive environment that values people for their skills, experiences, and unique perspectives. That's why we hope you'll apply even if you don't check every box listed in the job description. We want to know what only you can bring to Unify.