Job Description

10Pearls is an award-winning end-to-end digital innovation company that helps businesses imagine and build the future. We are proud to announce that 10Pearls was named as winner of the Best Tech Work Culture Timmy Award in Washington DC by Tech in Motion, recognized on the Inc. 5000 Fastest-Growing Companies List, and was ranked the #1 Most Diverse Midsize Company in Greater Washington. We partner with businesses to help them transform, scale, and accelerate by adopting digital and exponential technologies. Our work has ranged from creating highly usable, secure digital experiences, mobile and software products, to helping businesses modernize through cloud adoption and development and the digitalization of their business processes. Our clientele is highly diverse, including Global 1000 enterprises, mid-market businesses, and even high-growth start-ups. But those are just facts. What makes us unique is that we have a true heart and soul. We have a strong focus on a double bottom line and actively support and engage with the communities where we live and work to make the world a better place. In a nutshell, we believe in doing well, while doing good and know how to balance the two.

We are seeking a highly skilled and experienced Senior Machine Learning Developer to join our growing data and engineering team. The ideal candidate will have 5+ years of hands-on experience designing, developing, and deploying machine learning solutions from concept to production.

This role requires strong expertise in machine learning algorithms, data engineering, and scalable system design, along with the ability to collaborate cross-functionally and mentor junior team members.

Key Responsibilities

• Lead the end-to-end machine learning lifecycle: problem definition, data collection, feature engineering, model development, evaluation, deployment, and monitoring.

• Design, develop, and deploy scalable machine learning models in production environments.

• Build and maintain robust data pipelines for structured and unstructured data.

• Perform data analysis, experimentation, and model validation to ensure high performance and reliability.

• Optimize model performance, scalability, and inference speed.

• Collaborate closely with product managers, data engineers, software developers, and stakeholders to translate business requirements into ML solutions.

• Implement MLOps best practices, including CI/CD for ML models, versioning, monitoring, and retraining strategies.

• Ensure data security, governance, and compliance with relevant regulations.

• Conduct code reviews and maintain high coding standards and documentation.

• Research emerging ML techniques and recommend improvements or new solutions.

• Mentor junior machine learning engineers and provide technical leadership.

• Communicate progress, risks, and mitigation strategies to project managers and leadership.

Required Qualifications & Skills

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

• 5+ years of professional experience in machine learning development.

• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.

• Solid understanding of supervised and unsupervised learning, deep learning, and statistical modeling techniques.

• Experience with data preprocessing, feature engineering, and model evaluation methodologies.

• Hands-on experience with large datasets and distributed computing frameworks (Spark, Hadoop).

• Strong experience deploying models in production environments using REST APIs or microservices.

• Familiarity with MLOps tools such as MLflow, Kubeflow, or SageMaker.

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Strong understanding of databases (SQL and NoSQL).

• Experience with version control systems (Git) and CI/CD pipelines.

• Excellent analytical, problem-solving, and debugging skills.

• Strong communication and collaboration skills.