Posted at: 24 March
Senior AI Engineer
Company
Traackr is a global B2B SaaS platform headquartered in multiple locations including San Francisco and Paris, specializing in data-driven influencer marketing solutions for brands across various industries.
Remote Hiring Policy:
Traackr is a fully remote company hiring globally, with team members located in various regions including North America, Europe, and Asia-Pacific. We support remote collaboration across time zones (UTC-8 to UTC+10).
Job Type
Full-time
Allowed Applicant Locations
Worldwide
Salary
$120,000 to $170,000 per year
Job Description
We are looking for a Senior AI Engineer with 4–7 years of experience to design, build, and scale AI-powered systems and data infrastructure. This role combines advanced data engineering with production-grade machine learning, enabling the delivery of intelligent, data-driven products.
As a senior member of the team, you will take ownership of key AI and data initiatives, collaborate cross-functionally with Product Managers, Data Scientists, and Engineers, and help drive best practices in both AI/ML engineering and data platform development.
Responsibilities:
- Design, build, and deploy scalable machine learning and AI systems in production environments.
- Collaborate with Product Managers, Data Scientists and Engineers to lead the implementation of models and integrate them into data pipelines and agentic applications.
- Lead model performance monitoring, retraining workflows, and continuous improvement.
- Lead the implementation of data preprocessing and feature engineering pipelines for ML use cases.
- Lead to experimentation and testing of AI models to improve accuracy and performance.
- Develop, maintain, and optimize scalable data pipelines for analytics and machine learning workloads.
- Ensure data reliability, quality, and performance across data systems.
- Implement and maintain data ingestion pipelines from various internal and external sources.
- Build and improve internal tools that support data operations and data quality.
- Monitor and troubleshoot data pipelines to ensure consistent and timely delivery.
- Contribute to improving platform efficiency and scalability.
- Participate in code reviews and follow best practices in data and ML engineering.
- Document data pipelines, ML workflows, and system architecture.
- Contribute to evolving data and AI engineering best practices.
- Stay current with emerging tools, frameworks, and trends in AI, ML, and data engineering.
Requirements:
- 4–7 years of experience in AI Engineering, Machine Learning Engineering, or Data Engineering.
- Strong programming skills in Python, Java and SQL.
- Proven experience designing and building production-grade ML systems and data pipelines.
- Experience with Databricks, Apache Spark, or similar distributed data processing frameworks.
- Strong understanding of machine learning lifecycle (training, deployment, monitoring, retraining).
- Experience with cloud platforms (AWS, Azure, or GCP).
- Solid knowledge of data architecture, data modeling, and data warehousing concepts.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with MLOps practices and tools (e.g., MLflow, Airflow, CI/CD pipelines).
- Experience with version control (Git) and CICD development workflows.
- Strong problem-solving, communication, and cross-functional collaboration skills.
- Experience with LLMs, NLP, or generative AI applications.
- Experience building end-to-end AI products or data-driven platforms.
- Familiarity with real-time or streaming data pipelines.
- Experience with cost optimization and performance tuning in Databricks.
- Exposure to orchestration tools (Airflow, Dagster, etc.).
- Experience mentoring or onboarding junior team members.