Job Description

High Alpha is hiring a key team member for a new B2B SaaS startup in Indianapolis focused on generative AI in the marketing industry. This position will join High Alpha’s latest company, Backstroke. If you’re interested in working in a generative AI start-up and building from the ground floor–this is it!

About the Role: We are seeking a skilled Data Engineer with MLOps expertise to join our fast-growing startup. This role is ideal for a mid-level engineer who is eager to grow, take ownership of projects, and collaborate in a dynamic environment. The ideal candidate will be responsible for designing, building, and maintaining data pipelines that support machine learning (ML) models in production. This role requires strong experience in data engineering, cloud infrastructure, automation, and DevOps practices tailored for ML workflows . Candidates with experience in Artificial Intelligence (AI) and advanced machine learning solutions will be highly favored.

Key Responsibilities:

• Design, develop, and maintain scalable and reliable data pipelines to support ML models.
• Implement MLOps best practices , including model versioning, monitoring, and CI/CD automation for ML workflows.
• Work closely with data scientists, ML engineers, and software developers to integrate ML models into production environments.
• Ensure data quality, consistency, and security across pipelines and storage solutions.
• Automate data ingestion, transformation, and feature engineering processes.
• Deploy and manage containerized ML services using tools such as Docker and Kubernetes .
• Optimize cloud-based data architectures (AWS, GCP, or Azure) for cost and performance efficiency.
• Implement model monitoring and retraining pipelines to maintain model performance over time.
• Work extensively with Databricks for data processing, pipeline orchestration, and ML model deployment.
• Collaborate with DevOps and security teams to ensure compliance with data governance and security policies .

Required Skills & Qualifications:

• 2-4 years of experience in data engineering, with a strong focus on MLOps .
• Proficiency in Python, SQL, and distributed data processing frameworks (e.g., Spark, Apache Beam, or Kafka).
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their ML/AI services.
• Expertise in containerization and orchestration (Docker, Kubernetes, Airflow).
• Experience with CI/CD pipelines for ML models using tools like MLflow, GitHub Actions, or Jenkins .
• Strong understanding of feature stores, model registries, and versioning systems .
• Knowledge of data warehousing solutions such as Snowflake, BigQuery, or Redshift .
• Familiarity with Databricks for data engineering and MLOps workflows.
• Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK stack).
• Ability to work in agile teams , collaborate effectively, and communicate technical concepts clearly.

Preferred Qualifications:

• Experience with AI-driven solutions and deep learning frameworks (TensorFlow, PyTorch, etc.).
• Experience with data lake architectures and real-time data processing.
• Knowledge of Terraform or CloudFormation for infrastructure as code (IaC).
• Understanding of ethical AI and responsible AI deployment practices .

Why Join Us?

• Join a fast-growing startup working on cutting-edge AI/ML projects.
• Gain hands-on experience in a dynamic, high-growth environment with opportunities for ownership.
• Opportunities for continuous learning and professional development.
• Competitive salary, benefits, and flexible work arrangements.
• Inclusive and innovative work environment where your contributions make a real impact.

Compensation:

• $92K - $118K

Backstroke is an equal opportunity employer, and we value diversity at our company. We don’t discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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