Senior Machine Learning Engineer

Develop and optimize machine learning models for various applications. Preprocess and analyze large datasets to extract meaningful insights. Deploy ML solutions into production environments using appropriate tools and frameworks. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models. 3 years of experience in machine learning engineering or applied ML development. Experience building and scaling ML systems in production, particularly related to personalization, recommendations, ranking, or embeddings. Strong software engineering background with proficiency in Python, Java, or Scala. Hands-on experience with distributed systems and streaming technologies such as Kafka, Flink, Spark, or similar. Solid understanding of ML model lifecycle, including training, deployment, monitoring, and continuous improvement. Experience working with cloud-native architectures and modern CI/CD pipelines. Ability to collaborate effectively in cross-functional teams and communicate clearly with technical stakeholders. 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Several years of experience in designing, implementing, and deploying machine learning models. Experience with real-time inference platforms or feature stores. Familiarity with model monitoring, drift detection, and MLOps tooling. Exposure to deep learning frameworks (TensorFlow, PyTorch) or large-scale embeddings. Background with containerization and orchestration (Docker, Kubernetes). Experience supporting experimentation pipelines or A/B testing at scale.