Description:

Agiloft is seeking a skilled Senior MLOps Engineer to join their team focused on machine learning and generative AI.
The role involves collaborating with Data Scientists, Legal Knowledge Experts, Developers, and other Machine Learning Engineers to design, build, and maintain robust production machine learning infrastructure and tooling.
Responsibilities include building and maintaining end-to-end machine learning pipelines, from data ingestion to model deployment and monitoring.
The engineer will design, implement, and optimize infrastructure for rapid prototyping, continuous integration, deployment, and model evaluation.
Monitoring and maintaining production machine learning systems to ensure reliability, scalability, and performance is a key responsibility.
The position also involves providing technical guidance and mentorship to junior team members and fostering knowledge sharing within the MLOps and Data Science teams.
Staying updated with the latest advancements in MLOps, cloud technologies, and generative AI to identify and implement best practices is essential.
The engineer will set and enforce standards for code quality and best practices across the data science and engineering organizations.
Other duties may be assigned as needed.

Requirements:

Proven experience deploying and maintaining machine learning models in production environments is required.
Candidates must demonstrate the ability to gather requirements, design systems, and scope and plan projects effectively, focusing on the entire machine learning lifecycle.
Experience with REST API design and implementation, preferably using frameworks such as Flask or FastAPI, is necessary.
Proficiency in Python, including general-purpose programming and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch, is required.
Experience in building and scaling machine learning pipelines and infrastructure, including data gathering, feature engineering, model training, and deployment workflows, is essential.
Proficiency with cloud platforms, preferably AWS, and tools like SageMaker or Lambda is required.
Strong communication skills are necessary to effectively collaborate with diverse teams, including product managers, engineers, and data scientists.
Familiarity with CI/CD tools and practices as they apply to machine learning workflows is important.
Experience with modern containerization tools such as Docker and Kubernetes is required.

Agiloft offers a working environment that supports a healthy work/life balance, including floating holidays and a quarterly wellness day with no questions asked.
The company promotes a diverse and inclusive workplace, encouraging individuals from all walks of life to bring their authentic selves to work.
Employees are supported through multiple Employee Resource Groups (ERGs).
Agiloft is committed to an environment of acceptance, ensuring that all employment decisions are based on business needs and individual qualifications without regard to personal characteristics.
Applicants from underrepresented groups such as minorities, veterans, or individuals with disabilities are encouraged to apply.