Principal Machine Learning Engineer

• 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 deploying, monitoring, and iterating machine learning models in production.

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 or 1-800-671-6898.

Originally posted on Himalayas

• Ability to break down and communicate complex, highly technical concepts to audiences of varying technical understanding
• 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.)
• Knowledge of at least one cloud platform (e.g. AWS) and its relevant services (e.g. EMR, S3, and SageMaker).