CalTek is a Los Angeles & Orange County staffing agency specialized in recruiting IT and Software Engineers for a variety of industries. Our client is a cutting-edge technology company pioneering advancements in artificial intelligence (AI) and machine learning (ML) with a bold mission: to create emotionally intelligent AI systems capable of understanding, interpreting, and expressing human emotions. By combining deep learning, natural language processing (NLP), computer vision, and affective computing, their goal is to make human–machine interactions more empathetic, intuitive, and natural.

As part of the core engineering team, you will design and build the back-end infrastructure that powers emotion-aware AI applications, supporting real-time analytics, neural network processing, large-scale data pipelines, and cloud-native microservices architectures.

Typical Duties and Responsibilities

As a Back-End Developer (AI/ML Systems), you will:

  • Architect, develop, and optimize server-side APIs, databases, and microservices that support AI-driven platforms.
  • Build scalable cloud-native infrastructures (AWS, Azure, GCP) for training and deploying deep learning models.
  • Implement secure and efficient RESTful APIs and GraphQL endpoints for integration with front-end and mobile applications.
  • Design and maintain data storage systems (SQL, NoSQL, distributed databases) optimized for large-scale ML datasets.
  • Develop and deploy real-time data pipelines for emotion recognition, speech analysis, and natural language understanding.
  • Collaborate with AI researchers and data scientists to productionize machine learning models (TensorFlow, PyTorch, Scikit-learn) into scalable applications.
  • Ensure compliance with MLOps best practices, building CI/CD pipelines with tools such as Jenkins, GitLab, Docker, Kubernetes, and Terraform.
  • Optimize system performance for low-latency inference in real-time emotion-aware AI systems.
  • Implement security standards and protocols (OAuth2, JWT, TLS/SSL) to ensure data privacy, ethical AI usage, and regulatory compliance (GDPR, CCPA, ISO/IEC 27001).
  • Participate in Agile/Scrum development cycles, sprint planning, backlog grooming, code reviews, and daily standups.

Education

  • Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related field required.
  • Master’s degree in Computer Science, Artificial Intelligence, or Data Engineering preferred.

Required Skills and Experience

  • 5+ years of professional back-end development experience with a focus on scalable AI/ML platforms.
  • Strong proficiency in server-side programming languages:
    • Python, Java, C#, Go, Rust, or Node.js.
  • Advanced experience with databases:
    • Relational (MySQL, PostgreSQL, Oracle)
    • NoSQL (MongoDB, Cassandra, DynamoDB, Redis, Elasticsearch).
  • Hands-on expertise in cloud infrastructure: AWS (EC2, Lambda, S3, SageMaker), Azure (AKS, Functions, Cosmos DB), GCP (BigQuery, Vertex AI, Kubernetes Engine).
  • Deep understanding of microservices, event-driven architectures, and distributed systems.
  • Experience deploying and maintaining machine learning models in production (MLOps).
  • Familiarity with containerization and orchestration: Docker, Kubernetes, Helm, Istio.
  • Strong knowledge of API design and integration, authentication/authorization, and security protocols.
  • Excellent problem-solving skills, debugging, and performance optimization experience.

Preferred Qualifications

  • Previous experience in AI/ML product development, especially with emotion recognition, NLP, or computer vision applications.
  • Familiarity with streaming data frameworks: Apache Kafka, Apache Flink, Spark Streaming.
  • Exposure to DevSecOps and secure coding practices in regulated AI/healthtech/fintech environments.
  • Working knowledge of data visualization tools (Grafana, Kibana, Tableau, Power BI) for monitoring AI system performance.
  • Understanding of ethical AI frameworks and compliance with ISO/IEC AI standards.
  • Certification(s) in Cloud Engineering (AWS Solutions Architect, Google Cloud Professional Engineer, Azure Developer Associate) a plus.