Machine Learning Engineer

AboutFlatiron is a global remote software development company with engineers located around the world. We unite experts from diverse backgrounds and experiences in a collaborative culture to deliver exceptional products and services for our clients. As a forward-thinking software engineering company, we provide industry-leading solutions to complex problems in both the US and the UK. Operating in a fast-paced, agile environment, we specialize in software consulting for our clients. We offer a stimulating and rewarding environment for our team members. We value innovation, continuous learning, and professional growth, and we strive to create a workplace where everyone can thrive. Join us at Flatiron and be a part of a team that is shaping the future of software development.Job SummaryThis is a full-time fully remote working opportunity where you will be working as part of a Scrum team which requires working closely with other software engineers, stakeholders and contributors on the project. Working with respect to the US timezone is a requirement for the position. Attending meetings, being actively involved in the decision making process and collaborating with all of these stakeholders are essential parts of this position.Key ResponsibilitiesDesign, develop, and deploy scalable, production-ready machine learning systems and pipelines end-to-end.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 model training, serving, monitoring, and lifecycle management.Lead the data preparation and feature engineering process, ensuring data quality, integrity, and scalability.Implement and optimize ML models — including supervised, unsupervised, deep learning, NLP, and recommendation systems — with a focus on performance, accuracy, and reliability.Integrate models into backend services and APIs, ensuring seamless interaction with applications and end users.Contribute to MLOps workflows, including CI/CD for ML, model registry, experiment tracking, and automated retraining.Stay ahead of emerging trends in AI/ML, evaluating new research, frameworks, and tools, and applying them to enhance our products.Provide technical leadership and mentorship to junior engineers, guiding best practices across the ML lifecycle.Minimum QualificationsAdvanced written and oral English proficiency.Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.7+ years of professional experience designing, building, and deploying machine learning models in production environments.Expert proficiency in Python and ML libraries/frameworks such as TensorFlow, PyTorch, and scikit-learn.Strong experience with data processing and analysis tools (Pandas, NumPy, SQL) and data pipeline orchestration.Solid understanding of machine learning theory, algorithm selection, feature engineering, and model evaluation.Proven experience deploying ML systems on cloud platforms (AWS, GCP, or Azure).Hands-on experience with MLOps, containerization (Docker), and orchestration (Kubernetes).Strong track record of delivering ML solutions integrated into real products or services at scale.Preferred QualificationsExperience with large language models (LLMs), RAG pipelines, or agentic AI systems.Expertise in deep learning, NLP, time-series forecasting, or computer vision.Experience with tools such as MLflow, Kubeflow, SageMaker, or similar model-ops platforms.Contributions to open-source AI/ML projects or publications in the field.Familiarity with data engineering workflows, ETL pipelines, and real-time data processing.BenefitsYearly Office Allowance BudgetMacbook Purchase SupportWellbeing SupportIf you are a good fit for the position, please apply through .We only accept CVs that are in English.Flatiron has a zero tolerance to discrimination policy. In this regard, during the course of the evaluation of your job application and all your employment relation, if any, all discriminatory factors such as race, sex, sexual orientation, social gender definitions/roles, color, national or social background, ethnicity, religion, age, disablement, political opinion or any status that is protected under law shall be disregarded.