AI/ML Software Engineer

Responsibilities

• Build and implement AI/ML features end-to-end: data ingestion, feature

engineering, model training, evaluation, and deployment

• Develop and maintain RAG pipelines and LLM-powered applications using vector

stores, embeddings, and orchestration frameworks

• Create AI agents and integrations using Model Context Protocol (MCP) to

connect LLMs with internal tools and data sources

• Build classification models for brand safety, fraud detection, and content

categorization to improve targeting and reporting

• Train prediction and optimization models for adtech/martech needs including

CTR prediction, conversion forecasting, pricing optimization, and campaign

performance

• Develop backend services in Python that expose AI capabilities via APIs to

product and frontend teams

• Experiment with different model architectures (tree-based, neural networks,

LLMs) and evaluate trade-offs on accuracy, latency, and cost

• Implement monitoring and evaluation systems, including A/B tests, metrics

tracking, and model performance dashboards

• Collaborate with data, platform, and product teams to integrate AI/ML solutions

into core workflows

• Stay current with the AI/ML ecosystem and bring practical ideas to the team

Qualifications

• Bachelor or Master's degree in Computer Science, Statistics, Mathematics,

Engineering, or related field

• 2-5 years of professional experience in software engineering, ML engineering, or

data science

• Strong proficiency in Python and experience with ML frameworks (scikit-learn,

XGBoost, PyTorch, TensorFlow, or similar)

• Hands-on experience building applications with LLMs, prompt engineering, and

RAG patterns

• Solid understanding of machine learning fundamentals, statistics, and model

evaluation

• Experience with SQL and working with structured/unstructured data at scale
• Familiarity with APIs, backend development, and software engineering best

practices (Git, testing, CI/CD)

• Understanding of cloud platforms (AWS, GCP, or Azure) and containerization
• Experience with vector databases, search technologies, or big data tools (Spark,

Airflow, Kafka) is a plus

• Exposure to adtech/martech domains (advertising, marketing analytics,

campaign optimization) is a plus

• Strong communication skills and comfort working in a distributed, cross-

functional team

• Flexible with working hours to enable collaboration across time zones

Must have skills

• python
• ML Frameworks
• SQL
• RAG Patterns
• API's
• Backend Developmet
• Git, testing, CI/CD
• Adtech

Good to have skills

• Spark
• Airflow
• Kafka
• Martech
• Cloud Platforms
• AWS
• GCP
• Azure