Machine Learning Software Engineer (Contract-To-Perm)

Join us for an exciting opportunity to revolutionize the sustainable footwear industry using cutting-edge artificial intelligence with EarthDNA! As a Machine Learning Software Engineer on our team, you’ll be at the forefront of implementing advanced AI techniques in production environments that fundamentally transform how consumers engage with the cycle of sustainable footwear. This role combines the challenges of production-scale ML engineering with the meaningful impact of advancing sustainability in fashion. Please note that this is a contract role which requires work authorization for the Boston, MA, USA area. Key Responsibilities
Design, develop, and deploy machine learning models and systems at scale
Build robots ML infrastructure and pipelines for training, evaluation, and deployment
Collaborate with cross functional teams including data engineers and product management
Optimize model performance, latency, and resource utilization for production environments
Conduct code reviews and establish best practices for ML engineering
Stay current with the latest ML research and technologies, evaluating their applicability to business problems.
Collaborate cross-functionally with software engineers, design engineers, material scientists, and industry specialists across the globe to develop and deploy mobile and desktop applications. Required Qualifications
Active GitHub repository or portfolio demonstrating relevant code contributions, personal projects, or open-source work available for review during the application process.
Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent work experience with a demonstrated track record in the field)
3+ years of experience with software engineering for machine learning
Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
Proven track record of deploying ML models to production environments
Deep understanding of ML algorithms and deep learning architectures
Experience with distributed computing frameworks (Spark, Ray) and cloud platforms (AWS)
Proficiency in software engineering best practices including testing, CI/CD, and version control
Strong problem-solving skills and ability to work independently in complex, ambiguous technical challenges Preferred Qualifications
Advanced degree (MS/PhD) in Machine Learning, Computer Science, or related field
Experience with MLOps tools and practices (SageMaker, MLflow, Kubeflow)
Knowledge of model optimization techniques (quantization, pruning, distillation)
Experience with large-scale data processing and feature engineering
Familiarity with containerization (Docker, Kubernetes) and microservices architecture Technical Skills
Programming Languages: Python, Java, C++, or Scala
ML Frameworks: TensorFlow, PyTorch, Keras, XGBoost
Data Processing: Pandas, NumPy, Spark, SQL
Cloud Platforms: AWS (SageMaker, EC2, S3)
Tools: Git, Docker, Kubernetes, Airflow Equal Opportunity Statement EarthDNA is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.