- Company Name
- TechTree
- Job Title
- Founding Machine Learning & Data Engineer (Forward-Deployed)
- Job Description
-
Job Title: Founding Machine Learning & Data Engineer (Forward‑Deployed)
Role Summary:
Lead end‑to‑end design, training, and deployment of machine‑learning models for enterprise customers while architecting scalable data infrastructure. Work directly with clients to translate business problems into production‑grade ML systems, and partner with leadership to define AI strategy.
Expectations:
- Deliver high‑quality predictive models for structured and unstructured data within tight product timelines.
- Build and maintain robust data pipelines, feature stores, and semantic layers that enable real‑time ML feedback.
- Provide client‑facing technical leadership, from requirement gathering to production integration.
- Champion MLOps practices, ensuring model versioning, monitoring, retraining, and interpretability.
- Drive continuous improvement of ML architecture across the organization.
Key Responsibilities:
1. Design and implement regression, classification, clustering, and deep‑learning models (PyTorch, TensorFlow, scikit‑learn).
2. Create and optimize ETL workflows, schema models, and data pipelines for large‑scale enterprise datasets.
3. Integrate machine‑learning models into client systems, including API delivery and monitoring dashboards.
4. Develop feature engineering pipelines, embeddings, and knowledge‑graph interfaces.
5. Deploy MLOps tooling (Weights & Biases, MLflow, Vertex AI, SageMaker) for model lifecycle management.
6. Collaborate with executives to shape the company’s AI and data strategy.
7. Mentor and guide cross‑functional teams on best practices in ML and data engineering.
Required Skills:
- 7–10+ years of experience in machine‑learning and data‑engineering roles.
- Expertise in supervised/unsupervised learning, optimization, evaluation, feature engineering, clustering, and embeddings.
- Deep knowledge of data modeling, ETL, schema design, and modern data stacks.
- Proficiency with PyTorch, TensorFlow, scikit‑learn, and MLOps platforms (Weights & Biases, MLflow, Vertex AI, SageMaker).
- Strong communication and client‑facing capabilities.
- Ability to thrive in autonomy‑driven, fast‑paced environments.
- Systems thinking and high technical curiosity.
Required Education & Certifications:
- Bachelor’s (or higher) degree in Computer Science, Data Science, Machine Learning, or related field.
- Certifications in cloud data platforms or ML operations (e.g., AWS Certified Machine Learning, Google Cloud Professional Data Engineer) are advantageous.