Machine Learning Engineer

Key Skills

Algorithms, Amazon EMR, Anomaly detection, AWS Sagemaker, Clustering, Construction, CSS3, Data Classification, Keras software library, MxNet, PyG- PyTorch Geometric, Python Programming, Regression Analysis, SQL Server, TensorFlow

Job Description

ConnectWise is the world's leading software company dedicated to the success of IT Solution providers. As a company our vision is to power a thriving IT ecosystem that transforms what's possible for SMBs. How we do this is by empowering IT solution providers with unmatched software, services, and community to achieve their most ambitious vision of success

ConnectWise provides a work environment where each colleague is valued for their perspectives, skills and talents, is treated respectfully, can communicate openly and is encouraged to develop to their full potential as a contributor to the success of the company and the communities we serve. We value our colleagues and offer a competitive benefits package including medical, retirement investment plans, flexible time away, community volunteer opportunities, master's assistance program and colleague recognition programs.

General Summary:

The Machine Learning Engineer will have the responsibility of working on the machine learning pipelines that power ConnectWise's platform. Through shipping production machine learning models, this individual will contribute towards delivering thoughtful experiences for our partners through machine learning services. This individual will contribute towards the development of cutting-edge AI-based features for IT solution providers across the domains of business management, unified monitoring and security management. This position presents an exciting opportunity to work with large-scale data across a variety of use cases that include natural language processing, telemetry-based time series analysis, and computer vision.

Essential Duties and Responsibilities:

• Partner with product managers, software engineers and data science professionals to deliver production machine learning services powering the ConnectWise platform
• Research and develop machine learning services to be consumed by one or more product categories
• Design and maintain machine learning infrastructure in coordination with DevOps and Data Engineering
• Inform, influence, support, and execute on product decisions and product launches through deep collaboration with Product Owners
• Work with cross-functional teams, including Product Engineering and Data Engineering, to ensure that proper data pipelines are established to ensure availability of high quality data
• Spread best practices throughout Product and Engineering teams through advocacy of machine learning best practices

Knowledge, Skills, and/or Abilities Required: 

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions

• Demonstrated 3+ years experience with writing ML training/inference code (e.g. Python) and taking machine learning models to production
• Able to take a hands-on roles in the design and deployment of machine learning and deep learning services utilizing modern ML frameworks like Tensorflow, Keras, PyTorch, MXNet, etc.
• Deep knowledge of machine learning algorithms and techniques (Regression, clustering, anomaly detection, classification), including their selection and application within the ML model development lifecycle
• Exhibit a passion for pioneering ML solutions within a software solutions environment
• Must be able to interpret business requirements as translate into technical deliverables with limited direct supervision
• Must be able to break down and communicate complex, highly technical concepts to audiences of varying technical understanding
• Proficiency in SQL and/or other data manipulation languages as necessary to construct ML datasets for development
• Proficiency in version control systems such as Git
• Nice to have: experience building software on cloud computing platforms using services such as Amazon EMR, S3 and SageMaker or competitor analogs
• Nice to have: proficiency in big data processing tools such as Apache Spark
• Nice to have: understanding of MLOps tool chain and processes for maintaining complex ML systems in production

Educational/Vocational/Previous Experience Recommendations:

• Bachelor's in computer science, mathematics, statistics, engineering or comparable field of study (MS or PhD preferred)
• 3-7 years of experience in a role working in a programmatic data science or machine learning role
• Experience deploying, monitoring and iterating upon machine learning models in production

Working Conditions:

• Remote, hybrid and/or professional office environment
• Able to work morning US Eastern Time hours to collaborate with distributed teams in US, Europe, India and Rest of World
• Less than 10% travel required