Senior Machine Learning Engineer

C the Signs; Boston (MA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Competitive salary and benefits

Flexible working arrangements

Continuous learning opportunities

Job summary

C the Signs is seeking a Machine Learning Engineer in Boston to develop and deploy large language models within healthcare. Responsibilities include data preprocessing, model training, and collaboration with clinicians to impact patient outcomes. The ideal candidate has 5+ years in machine learning, strong Python skills, and experience with healthcare data. They offer a competitive salary, flexible hybrid work options, and opportunities to work on life-changing AI technology.

Qualifications

• 5+ years of experience in Machine Learning Engineering or similar role.
• Proven experience with large-scale data preprocessing and model training.
• Experience with GPU/TPU optimization and distributed training.

Responsibilities

• Clean and prepare large, complex healthcare datasets.
• Design, train, and fine-tune LLMs on healthcare data.
• Evaluate model performance and implement optimization strategies.
• Develop and maintain robust data and ML pipelines.
• Collaborate with data scientists and clinicians to integrate models.
• Stay updated with advancements in machine learning.

Skills

Data preprocessing

Model training & fine-tuning

Model evaluation & optimization

Collaboration

Research & development

Problem-solving

Communication skills

Ability to work independently

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Python

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

GCP

AWS

Job description

Position Summary

The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data preprocessing, model training, and fine-tuning using large-scale healthcare datasets. This role requires a strong understanding of Large language models, machine learning principles, data engineering, and experience working with sensitive healthcare data.

Key Responsibilities

• Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets for machine learning model development. This includes handling missing values, outlier detection, feature engineering, and data normalization. Identify, collect, and curate relevant, industry-specific datasets for model retraining. Format data appropriately for the chosen LLM and training pipeline
• Model Training & Fine-Tuning: Design, train, and fine-tune various LLMs on extensive healthcare data to solve specific clinical or operational problems. Set up and manage the training environment, including GPU instances and required software. Train and fine-tune pre-trained LLMs on the custom dataset to achieve specific goals. Experiment with and fine-tune hyperparameters such as learning rate, batch size, and training epochs to optimize model performance. Integration of structured + unstructured data (multi-modal/multi-input models)
• Model Evaluation & Optimization: Evaluate model performance using appropriate metrics, identify areas for improvement, and implement optimization strategies.
• Pipeline Development: Develop and maintain robust and scalable data and ML pipelines for model training, inference, and deployment.
• Collaboration: Work closely with data scientists, clinicians, and software engineers to understand requirements, integrate models into production systems, and ensure data privacy and security compliance.
• Research & Development: Stay up-to-date with the latest advancements in machine learning and healthcare AI, and explore new technologies and methodologies to enhance our solutions.
• Documentation: Maintain clear and comprehensive documentation of models, data pipelines, and experimental results.

Requirements

• Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
• Experience:
  • 5+ years of experience in Machine Learning Engineering or a similar role.
  • Proven experience with large-scale data preprocessing, LLM/model training, and fine-tuning.
  • Experience with distributed training (PyTorch Distributed, DeepSpeed, Ray, Hugging Face Accelerate).
  • Experience with GPU/TPU optimization, memory management for large language models.
  • Experience working with healthcare data is highly desirable.
• Technical Skills:
  • Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
  • Strong understanding of various machine learning algorithms, Large Language Models, and deep learning architectures.
  • Experience with cloud platforms (e.g., GCP, AWS) and distributed computing frameworks (e.g., Spark) is a plus.
  • Familiarity with MLOps practices and tools.
• Soft Skills:
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Ability to work independently and as part of a team in a fast-paced environment.
• Work Authorization:
  • Must be a US Citizen, Green Card holder, or currently in the US have valid H1B visa

Benefits

Joining C the Signs is not just about building AI; it’s about shaping the future of healthcare. If you are a technical leader with an unshakable belief in the power of AI to save lives and the ability to make it happen at scale, this is your opportunity to create a tangible, global impact.

• Competitive salary and benefits package.
• Flexible working arrangements (remote or hybrid options available).
• The opportunity to work on life-changing AI technology that directly impacts patient outcomes.
• Join a team that combines cutting-edge innovation with a mission to save lives and improve health equity.
• Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.