Develop and maintain backend services using Python and frameworks like Django, Flask, or FastAPI.

Design and implement RESTful APIs and integrate with third-party services.

Collaborate with data science teams to deploy machine learning models into production environments.

Optimize application performance and scalability for AI-driven features.

Implement data pipelines for model training and inference.

Write clean, maintainable, and well-documented code following best practices.

Ensure security, testing, and CI/CD automation for AI-enabled applications.

Monitor and troubleshoot production systems for uptime and reliability.

5+ years of experience in backend development with a strong focus on Python.

Hands-on experience with AI/ML model integration in production systems.

Proficiency in Django, Flask, or FastAPI.

Strong knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB).

Familiarity with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).

Experience with data processing, ETL pipelines, and asynchronous programming.

Knowledge of Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure).

Strong understanding of API security, authentication, and scalable architecture.

Experience with MLOps tools (MLflow, Kubeflow).

Familiarity with microservices architecture.

Knowledge of data engineering and big data technologies (Spark, Hadoop).

Exposure to DevOps practices and infrastructure as code.

Playwright for end-to-end testing.

Cypress for UI and integration testing.

JavaScript TypeScript for building and maintaining automated tests.

Design, implement, and maintain automated test scripts using JavaScript and TypeScript.

Ensure quality across web applications and APIs.

Collaborate with cross-functional teams to define acceptance criteria and improve processes.

Detect, document, and track bugs.

Contribute to continuous integration and delivery pipelines.

Advocate for best practices in QA and test automation.

3+ years of professional experience in QA Automation.

1+ year of hands-on experience with Playwright in real projects.

Experience with Cypress or similar testing frameworks.

Strong coding skills in JavaScript and TypeScript.

Solid knowledge of QA methodologies, tools, and processes.

Familiarity with CI/CD pipelines and version control (Git).

Excellent communication and teamwork skills.

Fully bilingual English/Spanish preferred.

Architect and implement a scalable, high-performance machine learning platform to support model development, deployment, monitoring, and analysis for both predictive and Generative AI models.

Lead the technical strategy and evaluation for our Generative AI infrastructure. This includes assessing the trade-offs between managed services and self-hosted open-source models, defining our LLM hosting strategy, and validating the end-to-end architectural approach for scalable, reliable AI features.

Ensure the platform supports a wide range of ML use cases, including real-time prediction serving, batch processing, and model experimentation.

Design and implement robust LLM orchestration for advanced applications, enabling the integration of our proprietary predictive models with LLMs to power new insights and workflows.

Optimize system performance and model latency to ensure robust, low‑latency inference across distributed systems, with a specific focus on the unique challenges of LLM serving.

Identify bottlenecks, evaluate, and integrate new technologies and tools.

Collaborate closely with data scientists to productionize both traditional predictive models and novel Generative AI solutions, focusing on systems that combine proprietary model outputs with LLMs to create actionable insights.

Contribute to the overall quality of the codebase, ensuring maintainability and best practices.

Drive ML / DS best practices, give technical recommendations on challenging problems.

Bachelor Degree in Computer Science, Software Engineering, or a related field.

4-5 years of experience building and managing production-level machine learning platforms and infrastructure, with a focus on model deployment, optimization, and scalability.

Demonstrated ability to improve the performance, reliability, and cost-efficiency of ML systems.

Strong experience with cloud-based ML infrastructure (AWS, GCP, Azure) and MLOps practices.

Nice to have and/or equivalent combination of education and experience such as a Master Degree or PhD in Computer Science, Data Science, Mathematics, Statistics, or related quantitative field.

Core Programming amp; Machine Learning:

• Proficiency in Python and deep experience with its data science and ML ecosystem (e.g., PyTorch, TensorFlow, scikit-learn, Pandas, NumPy).
• Hands-on experience with Generative AI frameworks and libraries such as LangChain, LlamaIndex, or Hugging Face Transformers.

MLOps Infrastructure:

• Expertise in building and maintaining MLOps infrastructure, including containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for both traditional ML models and LLM-based applications.
• Proven skill in managing cloud resources using Infrastructure as Code (Terraform).

Cloud Platforms Services:

• Extensive hands-on experience with cloud platforms, particularly AWS. Required experience with core services (S3, EC2, Lambda) and ML services (SageMaker).
• Direct experience with or deep knowledge of managed Generative AI services like AWS Bedrock, Amazon Titan, or equivalents (e.g., Google Vertex AI, Azure OpenAI Service).

Data Systems Storage:

• Advanced proficiency in SQL for complex data extraction and transformation.
• Experience with a variety of data storage solutions, including relational databases, NoSQL databases, and vector databases (e.g., Pinecone, Weaviate, ChromaDB).

5+ years coding with C#, .NET/.NET Core, and Entity Framework

5+ years developing UIs with Angular, TypeScript, and JavaScript or similar technologies.

Solid communication skills. The ability to communicate ideas and progress clearly and succinctly.

Experience building micro frontends and accessible user experiences (WCAG) is a plus.

Experience with relational databases. NoSQL experience is a plus.

Awareness and understanding of design patterns and practices.

B.S. in Computer Science, CIS, Engineering, or related experience.

Maintain, improve, and support existing mobile applications across mobile platforms, with a focus on Android.

Design and develop new features using .NET MAUI, Blazor, C#, and XAML.

Ensure performance, usability, and stability of the app through regular updates and refactoring.

Integrate with backend services and databases (RESTful APIs, SQL Server).

Manage app deployment and updates to the Apple App Store and Google Play Store.

Write clean, maintainable, and testable code that follows best practices and design patterns, such as MVVM and DI.

Troubleshoot production issues and implement long-term solutions.

5+ years of professional experience in software development.

2+ years of experience building and maintaining mobile apps with .NET MAUI or Xamarin.Forms.

Demonstrated experience deploying apps to Google Play (private apps B2B).

Strong knowledge of C#, .NET Core, and SQL Server.

Experience with XAML-based UI development and MVVM architecture.

Proficient in integrating RESTful APIs and handling app lifecycle across platforms.

Familiarity with Git, CI/CD workflows, and Agile development practices.