AI/ML Engineer

At Trackier, we're revolutionizing the way businesses measure and optimize their marketing performance. As a leading Marketing Analytics & Attribution platform, we empower advertisers, agencies, and ad networks with powerful, real-time insights to drive growth and maximize ROI.

In today's complex digital landscape, understanding every touchpoint of the customer journey is paramount. That's where Trackier comes in. Our robust platform provides comprehensive tracking, detailed analytics, and precise attribution models, ensuring you have a clear picture of what's working and why. From performance marketing campaigns to influencer collaborations and beyond, we give you the tools to make data-driven decisions that propel your business forward.

We're passionate about transparency, efficiency, and delivering measurable results. Our commitment to innovation means we're constantly evolving our platform to meet the dynamic needs of the industry, helping our clients achieve their growth ambitions with confidence.

Position Summary: We are seeking a driven and analytically-minded AI/ML Engineer with 2-3 years of experience to join our growing team. In this role, you will play a crucial part in the end-to-end lifecycle of our AI solutions, from understanding and preparing complex datasets to developing, deploying, and optimizing robust machine learning models. You will leverage your strong data analysis skills to identify patterns, generate insights, and translate them into effective AI strategies that drive business value. You will be working with LLM integrations where necessary to generate insights from data and enhancing chatbots using RAG and similar tech.

Key Responsibilities:

• Data Understanding & Preparation: Collaborate with data stakeholders to understand business problems and data sources. Perform data loading, cleaning, and preparation, including handling missing values, data type conversions, and ensuring data integrity for large datasets.
• Feature Engineering: Identify, extract, and transform relevant features from raw data to optimize model performance.
• Model Development: Design, develop, train, and evaluate machine learning models (including deep learning, natural language processing,etc., as relevant to our domain) for various applications.
• System Integration: Integrate AI models into existing production systems and applications, ensuring scalability and reliability.Performance Optimization: Continuously monitor, analyze, and improve the performance, accuracy, and efficiency of AI models in production.
• Insight Generation & Communication: Translate complex analytical findings and model outputs into clear, concise, and actionable business insights and recommendations for end users.
• Research & Innovation: Stay abreast of the latest advancements in AI/ML research and actively explore new technologies and methodologies to enhance our capabilities.
• Deployment & MLOps: Contribute to the development and implementation of MLOps practices, including model versioning, CI/CD for ML, and model monitoring.
• Collaboration: Work closely with cross-functional teams, including product managers, software engineers to define requirements and deliver high-quality AI solutions.
• Documentation: Create clear and comprehensive documentation for models, code, and processes.

Requirements

• Experience: 2-3 years of professional experience as an AI Engineer, Machine Learning Engineer, or a similar role focused on building and deploying ML solutions.
• Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related quantitative field.
• Programming: Strong proficiency in Python and experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras).
• Data Manipulation & Analysis: Demonstrated strong skills in data loading, cleaning, manipulation, and preparation using Pandas and NumPy.
• EDA & Visualization: Proven ability to conduct exploratory data analysis and create effective visualizations using libraries to communicate insights.
• ML Fundamentals: Solid understanding of machine learning principles, algorithms (e.g., supervised, unsupervised, reinforcement learning), and statistical modeling.
• Software Engineering: Strong software engineering fundamentals, including experience with version control (Git), testing, and code review practices.
• Problem Solving: Excellent analytical and problem-solving skills with a keen attention to detail and the ability to derive actionable insights from data.
• Communication: Strong written and verbal communication skills, with the ability to explain complex technical concepts and present data-driven recommendations to both technical and non-technical stakeholders.

Preferred Qualifications:

• Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Familiarity with containerization technologies (Docker, Kubernetes).
• Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Sagemaker).
• Knowledge of distributed computing frameworks (e.g., Spark).
• Contribution to open-source projects or relevant publications.
• Experience with agile development methodologies.

Benefits

• Medical Insurance.
• 5 days working culture.
• Best in industry salary structure.
• Sponsored trips.