The job, in the employer's words
ConnectWise is an industry and Global leading software company with over 3,000 colleagues in North America, EMEA and APAC. As a community-driven software company dedicated to the success of technology solution providers, our suite helps over 45,000 of our partners manage their businesses better, sell more efficiently, automate service delivery, and remotely control technology so they can consistently deliver amazing customer experiences.
Our company is powered by our connections, our colleagues, and our community. And, we accept all kinds.
Game-changers, innovators, culture-lovers—and humankind.
We invite discovery and debate. We recognize key moments as milestones.
We see you and value you for your unique contributions. Our inclusive, positive culture lays the foundation to ensure every colleague is valued for their perspectives and skills, giving you the choice of how YOU make a difference.
Curious? Read this opportunity to learn how YOU can make a difference at ConnectWise!
General Summary:
The Principal Machine Learning Engineer is responsible for building Machine learning models based on diverse business requirements, setting up the pipelines, and assisting in delivering thoughtful experiences for our partners. This role works in partnership with cross-functional teams to contribute to the development of cutting-edge ML solutions.
Essential Duties and Responsibilities:
- Builds/ Optimizes machine learning models.
- Researches, analyzes, and documents findings.
- Assists in delivering production grade machine learning services that power the ConnectWise platform and products.
- Designs and maintains machine learning infrastructure.
- Informs, influences, supports, and executes on product decisions and product launches.
- Works with cross-functional teams to ensure that proper data pipelines are established to ensure availability of high-quality data.
Knowledge, Skills, and/or Abilities Required:
- Ability to work independently on projects and processes with close supervision.
- Broad theoretical knowledge of ML/ AI space and application development using generative AI including supervised fine-tuning, preference optimization (DPO), and reinforcement fine-tuning (RFT) of LLMs; parameter-efficient fine-tuning (LoRA/QLoRA); fine-tuning encoder models such as BERT/ModernBERT for text classification; and retrieval-augmented generation with embedding retrievers and cross-encoder rerankers.
- Strong grasp of model evaluation methodology (task-specific eval sets, LLM-as-judge, offline metrics, and online A/B testing) and experience building training-data, synthetic-data, and distillation pipelines for post-training.
- Ability to situationally adapt and understand new technology/processes as per business partner requirement.
- Strong programming skills in python and fluency in common libraries ( Hugging Face Transformers, TRL, PEFT, Sentence-Transformers, scikit-learn, etc.)
- Proficient in SQL and/or other data manipulation languages.
- Knowledge of big data processing tools such as Apache Spark.
- Proficiency in version controls systems such as Git.
- Knowledge of at least one cloud platform (e.g. AWS) and its relevant services (e.g. EMR, S3, and SageMaker).
- Ability to interpret business requirements and translate into ML deliverables.
- Ability to break down and communicate complex, highly technical concepts to audiences of varying technical understanding
Educational/Vocational/Previous Experience Recommendations:
- Bachelor degree in CS or related field required; Master’s or PhD preferred.
- 8+ years of relevant experience
- Experience writing code (e.g. Python) and taking machine learning models to production.
- Experience building software on cloud computing platforms.
- Experience deploying, monitoring, and iterating machine learning models in production.
Work Type: Remote
ConnectWise is an Equal Opportunity Employer, dedicated to building a diverse and inclusive workforce and providing a workplace free from discrimination and harassment. ConnectWise provides equal employment opportunities to all employees and applicants without regard to race, ethnicity, color, religion, age, sex (including pregnancy), sexual orientation, gender, gender identity or expression, ancestry, national origin, citizenship status, physical or mental disability, genetic information, military/veteran status, marital status, familial or parental status, or any other characteristic or status protected by applicable federal, state and local laws.
The statements above are intended to describe the general nature and level of work being performed by individuals assigned to this job. Other duties may be assigned as needed. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions of the job and/or to receive other benefits and privileges of employment. If you need a reasonable accommodation for any part of the application and hiring process, please contact us at talentacquisition@connectwise.com or 1-800-671-6898.
Requirements mentioned
- Ability to work independently on projects and processes with close supervision.
- Broad theoretical knowledge of ML/ AI space and application development using generative AI including supervised fine-tuning, preference optimization (DPO), and reinforcement fine-tuning (RFT) of LLMs; parameter-efficient fine-tuning (LoRA/QLoRA); fine-tuning encoder models such as BERT/ModernBERT for text classification; and retrieval-augmented generation with embedding retrievers and cross-encoder rerankers.
- Strong grasp of model evaluation methodology (task-specific eval sets, LLM-as-judge, offline metrics, and online A/B testing) and experience building training-data, synthetic-data, and distillation pipelines for post-training.
- Ability to situationally adapt and understand new technology/processes as per business partner requirement.
- Strong programming skills in python and fluency in common libraries ( Hugging Face Transformers, TRL, PEFT, Sentence-Transformers, scikit-learn, etc.)
- Proficient in SQL and/or other data manipulation languages.
- Knowledge of big data processing tools such as Apache Spark.
- Proficiency in version controls systems such as Git.
- Knowledge of at least one cloud platform (e.g. AWS) and its relevant services (e.g. EMR, S3, and SageMaker).
- Ability to interpret business requirements and translate into ML deliverables.
- Ability to break down and communicate complex, highly technical concepts to audiences of varying technical understanding
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