Senior AI/ML Engineer

This is a fully remote position, open to applicants in Pakistan.

📋 Description

• Design and implement features powered by LLM, such as conversational interfaces, AI agents, structured generation, and retrieval-augmented systems.

• Develop and sustain ML pipelines for tasks like prediction, anomaly detection, classification, and time-series analysis.

• Create backend APIs and services that connect data sources, models, and applications for clients.

• Work with both structured and unstructured data from relational databases, data warehouses, and external APIs.

• Enhance model performance and scalability for production environments, including monitoring and optimization.

• Collaborate with cross-functional teams (product, data, and engineering) to convert business requirements into technical solutions.

• Maintain code quality, documentation, and adhere to best practices for deployment, testing, and maintainability.

⛳️ Requirements

• Extensive experience with FastAPI (or similar asynchronous frameworks), including dependency injection, UV, Pydantic, and async/await patterns (including using thread pool executors for blocking operations).

• Strong grasp of REST API design principles, including multi-tenancy, pagination, filtering, JWT/OAuth2 authentication, and structured error management.

• Proficient in SQLAlchemy (including async sessions), handling raw parameterized queries, schema design, and migrations.

• Practical experience in integrating various LLM providers (e.g., OpenAI, Anthropic, AWS Bedrock, Ollama, Google Gemini, Snowflake Cortex) using provider abstraction layers.

• Familiarity with JSON response validation, extraction of markdown/code blocks, and fallback error handling (preferably using frameworks like Pydantic).

• Knowledge of prompt engineering strategies, including context injection, temperature/token tuning, and confidence scoring.

• Understanding of embedding-based retrieval and similarity scoring techniques.

• Experience with production-level agentic frameworks such as Pydantic AI (structured output generation and 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 for high-frequency sensor data.

• Experience with train/test splits, feature engineering, model evaluation (R², MAE, etc.), and experiment tracking (e.g., MLflow).

• Understanding when to integrate classical ML with LLM-based components (e.g., LLM-assisted labeling, embedding features in tree models).

• Strong database skills, 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 advantageous.

• Experience with Snowflake (including Snowpark, Model Registry, and Cortex) or similar platforms.

• Hands-on experience with AWS services such as Bedrock, ECS, and EC2.

• Proficient in Docker and CI/CD pipelines.

• Familiarity with S3 or equivalent object storage solutions.

• Ability to operate within VPN-gated infrastructure.

• Experience across various client environments or industries (consulting background preferred).

• Exposure to Industrial IoT or sensor data (high-frequency telemetry, signal processing).

• Experience in designing NL-to-SQL or text-to-query systems.

• Ability to manage multilingual data and implement internationalization.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health and wellness benefits.

• Opportunities for professional development and career growth.

• Flexible work arrangements and a collaborative work environment.