Description:

Concurrency is seeking a Senior Machine Learning Engineer to join their Data & AI team.
The role involves designing and engineering ML systems to address customer challenges in various sectors including Manufacturing, Retail, Agriculture, Education, and Hospitality.
The engineer will act as a technical thought leader, aligning technical solutions with customer and business needs.
Responsibilities include helping the data science team grow, demonstrating knowledge of ML approaches, and creating business value through model fitting.
The engineer will work with supervised, unsupervised, and deep learning methods, utilizing inferential statistics, time series, LLMs, or computer vision as needed.
Duties also include designing, engineering, testing, documenting, and explaining production ML systems using Azure, Python, SQL, and Git.
The role requires gathering input from non-technical stakeholders and senior IT leadership to plan projects and set scopes.
The engineer will frame complex problems, propose data-driven solutions, and lead technical design discussions.
The position involves using Big Data tools like Databricks, Spark, Azure, SQL, and Python for analyses and production solutions.
Responsibilities include fitting, tuning, testing, validating, and deploying ML models in an MLOps environment, as well as simplifying project discussions for customers.

Requirements:

Strong coding skills in SQL and Python, particularly with libraries such as pandas, numpy, scikit-learn, and Tensorflow/PyTorch are required.
Experience in designing and implementing LLM systems, including multi-agent systems and custom routing.
A minimum of 20 projects in cloud development is necessary, with Azure preferred but AWS and GCP acceptable.
Professional experience with Databricks/Spark and Docker/Kubernetes is required.
Candidates should have at least 7 years of experience managing ML systems from conception to maintenance.
Demonstrable thought leadership through an active GitHub, blog posts, or publications is essential.
A deep curiosity and motivation to tackle challenges, along with a willingness to propose improvements, are important traits.
The ability to communicate complex ideas simply to diverse audiences is necessary.
Proven success in managing end-to-end projects independently while knowing when to escalate or delegate is required.
Experience in a production MLOps setting and familiarity with tools for the ML lifecycle, including EDA, data preparation, and deployment, is essential.
Experience in data visualization to understand and persuade is also required.

Concurrency offers flexible work schedules to accommodate employees' needs.
Competitive compensation packages are provided to all employees.
Comprehensive benefits are available for employees and their families.
Team members have access to recognition programs to celebrate achievements.
The company provides extensive training opportunities for professional and personal growth.
Concurrency fosters a workplace that is innovation-driven and enjoyable, promoting collaboration and resilience.