Job Description

Principal-AI Engineer

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Job Summary:

Seeking a highly skilled and passionate AI Engineer to design, develop, and deploy cutting-edge artificial intelligence systems and machine learning models. The ideal candidate will possess a strong blend of software engineering expertise, data science principles and a deep understanding of AI/ML algorithms. You will play a crucial role in transforming complex business challenges into intelligent, data-driven solutions that drive innovation and enhance user experiences.

Responsibilities:

Design and Development:

+ Architect, design, develop, and deploy robust, scalable, and high-performance AI solutions and machine learning models (e.g., predictive analytics, natural language processing, computer vision, recommendation systems, generative AI).
+ Translate business requirements and research prototypes into production-ready AI applications.
+ Develop and implement efficient and optimized machine learning algorithms and neural network architectures.

Data Management and Engineering:

+ Collaborate with data scientists and data engineers to manage large datasets, including data collection, preprocessing, cleaning, transformation, and feature engineering.
+ Build and maintain data pipelines for training, validation, and deployment of AI models.
+ Ensure data integrity, quality, and security throughout the AI lifecycle.

Model Optimization and Deployment:

+ Optimize AI models for performance, accuracy, scalability, and efficiency, leveraging techniques like hyperparameter tuning and distributed computing frameworks.
+ Integrate AI solutions into existing software systems, products, and services through APIs, microservices, or embedded code.
+ Develop and maintain MLOps pipelines for continuous integration, continuous delivery (CI/CD), model versioning, monitoring, and retraining.

Research and Innovation:

+ Stay abreast of the latest advancements, research papers, and tools in AI, machine learning, and deep learning, and proactively propose their application to enhance existing solutions or develop new ones.
+ Conduct experiments, evaluate model performance, and troubleshoot AI-related issues to ensure reliability and accuracy.

Collaboration and Communication:

+ Work closely with cross-functional teams including data scientists, software engineers, product managers, and business stakeholders to define project requirements, gather insights, and ensure AI solutions align with business objectives.
+ Effectively communicate complex AI concepts and their business impact to both technical and non-technical audiences.
+ Participate in code reviews, design discussions, and collaborative problem-solving sessions.

Qualifications:

Education:

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.

Experience:

3 years of proven experience as an AI Engineer, Machine Learning Engineer, or similar role, with a strong portfolio of successful AI/ML projects.

Programming Proficiency:

Expert-level proficiency in programming languages commonly used in AI development, such as Python. Familiarity with other languages like R, Java, or C++ is a plus.

Mathematical and Statistical Foundations:

Solid understanding of mathematical concepts relevant to AI, including linear algebra, calculus, probability, and statistics.

Data Handling:

Experience with data preprocessing, feature engineering, and working with large datasets. Familiarity with big data technologies (e.g., Apache Spark, Hadoop) and database systems (SQL/NoSQL) is beneficial.

Cloud Platforms:

Experience deploying and managing AI models on cloud platforms (e.g., AWS SageMaker, Google Cloud AI Platform, Azure ML).

Software Engineering Practices:

Strong software engineering skills, including experience with version control systems (e.g., Git), agile development methodologies (Scrum/Kanban), and clean code practices.

Problem-Solving:

Excellent analytical, critical thinking, and problem-solving skills with a meticulous attention to detail.

Communication:

Exceptional communication and interpersonal skills, with the ability to articulate technical concepts clearly and collaborate effectively within a team environment.

Bonus Points (Preferred Qualifications):

Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes). Familiarity with ethical AI principles, bias detection, and explainable AI (XAI). Contributions to open-source AI projects or relevant publications. * Experience in Infrastructure, Real Estate, or E-commerce industry.