We are seeking a highly skilled AI / Machine Learning / Data Engineer to design, build, and deploy intelligent systems that power data-driven decision-making and automation. The ideal candidate has strong experience in machine learning models, data pipelines, and production-grade AI systems.
Key Responsibilities
- Design, develop, and deploy machine learning models for real-world applications
- Build and maintain scalable data pipelines for structured and unstructured data
- Collaborate with product, engineering, and business teams to define AI-driven solutions
- Train, evaluate, and optimize models using appropriate metrics and validation techniques
- Implement and maintain MLOps practices for model deployment, monitoring, and retraining
- Work with large datasets using distributed computing frameworks
- Integrate models into production systems via APIs and services
- Ensure data quality, governance, and compliance standards are met
- Continuously research and apply new AI/ML techniques and tools
Required Skills & Qualifications
- Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience with data processing tools (SQL, Pandas, Spark, etc.)
- Solid understanding of machine learning concepts (supervised, unsupervised, deep learning)
- Experience building and deploying models in production environments
- Familiarity with cloud platforms (AWS, Azure, or GCP)
- Knowledge of APIs, microservices, and backend integration
- Understanding of data structures, algorithms, and software engineering principles
- Experience with version control systems (e.g., Git)
Preferred Qualifications
- Experience with LLMs (Large Language Models) and prompt engineering
- Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow)
- Familiarity with containerization (Docker, Kubernetes)
- Experience with real-time data processing systems
- Background in statistics, mathematics, or related technical fields
- Prior experience in AI product development or startup environments
Nice-to-Have
- Experience working with recommendation systems, NLP, or computer vision
- Knowledge of feature engineering at scale
- Experience optimizing models for latency and performance
- Exposure to distributed systems architecture
Soft Skills
- Strong problem-solving and analytical thinking
- Ability to work independently and in cross-functional teams
- Clear communication of technical concepts to non-technical stakeholders
- Ownership mindset and attention to detail
- Adaptability in fast-paced environments
Pay: Up to $140,000.00 per year
Benefits:
Work Location: Hybrid remote in Chicago, IL 60617