Lead Machine Learning Engineer
Digital Turbine, Inc.23 hours ago
Responsibilities
- Lead the end-to-end architecture, design, deployment, and productionization of complex machine learning models and ML infrastructure.
- Translate ambiguous business problems into scalable ML engineering solutions and system specifications.
- Establish MLOps practices, operational standards, framework selections, and model monitoring and evaluation workflows.
- Build and optimize ML pipelines, training systems, robust features, feature stores, and scalable data ingestion systems.
- Drive model optimization, latency reduction, distributed training, and cost-efficient inference at scale.
- Implement monitoring for model drift, data quality, performance degradation, and production system health.
- Evaluate emerging ML technologies, architectures, and tools for organizational adoption.
- Collaborate with Data Engineering, DevOps, Platform, Security, product managers, domain experts, and executive stakeholders.
- Mentor P1–P3 Machine Learning Engineers through design reviews, code reviews, and pair engineering.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related quantitative field.
- 8+ years of professional machine learning engineering experience.
- Proven experience taking complex ML models from inception through high-scale real-time and batch production deployment.
- Deep expertise with PyTorch, TensorFlow, Jax, or comparable modern ML frameworks, plus traditional ML libraries such as Scikit-Learn and XGBoost.
- Hands-on experience with orchestration, containerization, and MLOps platforms such as Kubernetes, Docker, MLflow, Kubeflow, AWS SageMaker, or GCP Vertex AI.
- Strong proficiency in data structures, algorithms, object-oriented design, distributed systems, and CI/CD automation.
- Prior experience as a Technical Lead or Principal Contributor on high-impact engineering initiatives.
- Expertise in LLM orchestration, fine-tuning, retrieval-augmented generation, or modern generative AI systems.
- Familiarity with distributed computing engines such as Ray, Spark, or Dask and with high-throughput databases, vector databases, or feature stores.
- Ability to provide technical leadership, mentorship, and cross-functional alignment without formal direct-report administration.
Benefits
- Hybrid and flexible work environment.
- Comprehensive benefits package designed to support employee well-being.
- Global work environment serving customers and partners across North America, EMEA, APAC, and LATAM.
Tech Stack
Apache SparkAWSC++DockerGoogle Cloud PlatformKubernetesMLflowPythonPyTorchScalascikit-learnTensorFlowXGBoost
Categories
About Digital Turbine, Inc.
Digital Turbine builds a mobile growth and monetization platform that connects advertisers, app developers, carriers, and OEMs through on-device app discovery, ad delivery, and data-driven optimization. Its products include on-device placements (Ignite), a demand-side platform, offerwall, and content media services that drive user acquisition and ad revenue. The company is publicly traded on NASDAQ (APPS) and is headquartered in Austin, Texas.