Intelligent Machine Learning Developer

About UsWe are a remote software development company with a global presence.Our collaborative culture brings together experts from diverse backgrounds to deliver exceptional products and services.As a forward-thinking software engineering company, we provide industry-leading solutions to complex problems.We operate in a fast-paced, agile environment, specializing in software consulting for our clients.We offer a stimulating and rewarding work environment that values innovation, continuous learning, and professional growth.Job SummaryThis is a full-time fully remote opportunity where you will be working as part of a Scrum team.You will work closely with other software engineers, stakeholders, and contributors on the project.Working within the US timezone is required for this position.Attending meetings, being actively involved in the decision-making process, and collaborating with all stakeholders are essential parts of this role.Key ResponsibilitiesDesign, develop, and deploy scalable, production-ready machine learning systems and end-to-end pipelines on AWS.Partner with data scientists, software engineers, and product teams to define requirements, select algorithms, and deliver impactful ML solutions.Architect, optimize, and maintain ML infrastructure — including data ingestion, model training, deployment, serving, monitoring, and lifecycle management — using AWS services.Lead the data preparation and feature engineering process, ensuring data quality, integrity, and scalability across large datasets.Implement and optimize ML models (supervised, unsupervised, deep learning, NLP, recommendation systems) with a focus on performance, accuracy, and reliability.Build and manage robust data pipelines and orchestration workflows to support ML systems at scale.Integrate models into backend services and APIs, ensuring seamless interaction with applications and end users.Contribute to MLOps practices, including CI/CD for ML, model registries, experiment tracking, automated retraining, and infrastructure-as-code provisioning.Utilize Infrastructure-as-Code tools such as Terraform, AWS CDK, or CloudFormation to build and maintain scalable, secure ML infrastructure.Stay ahead of emerging trends in AI/ML, evaluating new research, frameworks, and tools to enhance product capabilities.Provide technical leadership and mentorship to junior engineers, guiding best practices throughout the ML lifecycle.