Job Title

We’re looking for a Machine Learning Engineer who operates at the intersection of data, engineering, and business outcomes. This role is not just about building models—it’s about deploying reliable, scalable ML systems that solve real-world problems and drive measurable impact.You’ll work closely with data scientists, product managers, and engineering teams to take models from experimentation to production—ensuring they perform, scale, and evolve with the business.Key ResponsibilitiesDesign, build, and deploy scalable machine learning models into production environmentsTranslate business problems into ML solutions with clear success metricsDevelop and maintain end-to-end ML pipelines (data ingestion → training → deployment → monitoring)Optimize model performance, latency, and cost efficiency in production systemsWork on feature engineering, model selection, and hyperparameter tuningImplement model monitoring, drift detection, and continuous retraining strategiesCollaborate with data engineering teams to ensure clean, reliable, and accessible dataEnsure ML systems follow best practices in versioning, testing, and reproducibilityContribute to architecture decisions for ML platforms and infrastructureRequired Skills & ExperienceStrong programming skills in PythonHands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learnSolid understanding of supervised and unsupervised learning techniquesExperience building and deploying models using REST APIs or microservicesFamiliarity with data processing tools (Pandas, NumPy, Spark)Experience with cloud platforms like Amazon Web Services, Google Cloud Platform, or Microsoft AzureUnderstanding of CI/CD pipelines and containerization (Docker, Kubernetes)Strong grasp of software engineering fundamentals (testing, version control, system design)Good to HaveExperience with MLOps tools (MLflow, Kubeflow, SageMaker)Exposure to deep learning, NLP, or computer vision use casesExperience working with large-scale distributed systemsKnowledge of data warehousing and big data ecosystems