Senior AI/ML Engineer

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🕒 April 3

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HR POD - Hiring Talent Globally

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

👥 HR Tech

🎯 Recruiter

🤝 B2B

HR Tech • Recruitment • B2B

HR POD is a leading premium global recruitment agency dedicated to elevating human resource management services. With a focus on helping companies strategize and build robust HR frameworks, HR POD specializes in recruitment, training, and performance management. They pride themselves on serving a diverse client base, particularly in the tech industry, and adopt a data-driven approach to optimize HR practices that align with organizational goals. Their commitment to integrity, customer satisfaction, and excellence positions them as a reliable partner in enhancing talent acquisition and retention strategies for businesses worldwide.

📋 Description

• Design and integrate LLM-powered features, including conversational interfaces, AI agents, structured generation, and retrieval-augmented systems. • Build and maintain ML pipelines for prediction, anomaly detection, classification, and time-series analysis. • Develop backend APIs and services connecting data sources, models, and client-facing applications. • Work with structured and unstructured data across relational databases, data warehouses, and external APIs. • Optimize model performance and scalability for production environments, including monitoring and fine-tuning. • Collaborate with cross-functional teams (product, data, and engineering) to translate business requirements into technical solutions. • Ensure code quality, documentation, and best practices for deployment, testing, and maintainability.

🎯 Requirements

• Strong experience with FastAPI (or equivalent async frameworks), including dependency injection, UV, Pydantic, and async/await patterns (including thread pool executors for blocking operations). • Solid understanding of REST API design, including multi-tenancy, pagination, filtering, JWT/OAuth2 authentication, and structured error handling. • Proficiency in SQLAlchemy (including async sessions), raw parameterized queries, schema design, and migrations. • Hands-on experience integrating multiple LLM providers (e.g., OpenAI, Anthropic, AWS Bedrock, Ollama, Google Gemini, Snowflake Cortex) using provider abstraction layers. • Experience with JSON response validation, markdown/code-block extraction, and fallback error handling (preferably using frameworks like Pydantic). • Knowledge of prompt engineering techniques, including context injection, temperature/token tuning, and confidence scoring. • Familiarity with embedding-based retrieval and similarity scoring. • Experience with production-grade agentic frameworks such as Pydantic AI (structured output generation, agents). • Strong experience with gradient boosting models (e.g., XGBoost, LightGBM), including GPU-accelerated training, hyperparameter tuning, and evaluation. • Expertise in segmentation, anomaly detection, and feature engineering on high-frequency sensor data. • Experience with train/test splits, feature engineering, model evaluation (R², MAE, etc.), and experiment tracking (e.g., MLflow). • Understanding of when to combine classical ML with LLM-based components (e.g., LLM-assisted labeling, embedding features in tree models). • Strong database knowledge, including complex schemas, JSONB, partitioned tables, row-level security, query optimization, and vector extensions (e.g., pgvector). • Familiarity with NoSQL databases like MongoDB and specialized databases such as Redis and Qdrant is a plus. • Experience with Snowflake (including Snowpark, Model Registry, and Cortex) or equivalent platforms. • Hands-on experience with AWS services such as Bedrock, ECS, and EC2. • Experience with Docker and CI/CD pipelines. • Familiarity with S3 or equivalent object storage solutions. • Ability to work within VPN-gated infrastructure. • Experience across multiple client environments or industries (consulting background preferred). • Exposure to Industrial IoT or sensor data (high-frequency telemetry, signal processing). • Experience in NL-to-SQL or text-to-query system design. • Ability to handle multilingual data and implement internationalization.