Staff Software Engineer – ML Applications/Remote

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Apetan Consulting, is seeking the following. Apply via Dice today!Job Title: Staff Software Engineer – ML ApplicationsLocation: RemoteExperience: 8–12 yearsJob SummaryWe are looking for a Staff Software Engineer to lead the design and development of machine learning–powered applications. This role blends strong software engineering fundamentals with applied machine learning, focusing on building scalable, production-grade ML systems. You will set technical direction, drive architectural decisions, and mentor engineers across teams.Key ResponsibilitiesDesign and build scalable ML-driven applications and servicesLead architecture for ML systems, including model serving, data pipelines, and APIsCollaborate with data scientists to productionize ML modelsDefine best practices for ML engineering, deployment, and monitoringEnsure reliability, scalability, and performance of ML systems in productionDrive technical strategy and influence engineering roadmapsReview code, mentor engineers, and elevate team standardsWork cross-functionally with product, data, and platform teamsRequired Skills & QualificationsStrong programming experience in Python (or similar languages)Deep understanding of software engineering principles and system designHands-on experience building and deploying ML models in productionExperience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)Knowledge of data pipelines and distributed systemsExperience with REST APIs, microservices, and backend developmentFamiliarity with cloud platforms (AWS, Google Cloud Platform, or Azure)Strong understanding of databases and data storage systemsPreferred QualificationsExperience with MLOps tools (e.g., MLflow, Kubeflow, Airflow)Knowledge of real-time inference and batch processing systemsFamiliarity with big data technologies (Spark, Kafka, Hadoop)Experience with containerization (Docker, Kubernetes)Background in applied AI domains (NLP, computer vision, recommendation systems)Leadership & ImpactSet technical direction for ML application developmentMentor senior and mid-level engineersInfluence cross-team architecture and engineering practicesDrive adoption of best practices in ML lifecycle managementSoft SkillsStrong leadership and decision-making abilityExcellent communication and stakeholder managementAbility to operate in ambiguity and drive outcomesNice to HaveExperience scaling ML systems to high-traffic production environmentsContributions to research, patents, or open-source ML projects