AI/Ml Engineer

Role & responsibilities

• Design, deliver, and optimize high-performance, large-scale applications, data pipelines, and ML service infrastructure with exceptional speed and reliability.
• Enhance core products by skillfully integrating, fine-tuning, and deploying advanced machine learning models for optimal performance and impact.
• Command the full software development lifecyclefrom initial design and architecture to coding, testing, deployment, and maintenancewhile producing clean, efficient, and documented code.
• Develop and execute sound technical strategies for complex projects, taking into account business goals, timelines, and long-term impact.
• Work closely with product managers and partners to translate business requirements into robust technical solutions, ensuring alignment across teams.
• Take ownership of cross-team engineering efforts and guide junior team members, setting a high standard for technical excellence and professional growth.
• Drive innovation by developing novel solutions to challenging problems and actively contribute to a culture of knowledge sharing by both teaching and learning from others.

Preferred candidate profile

• Masters or Bachelors degree in Computer Science or a related field with 10+ years of experience in building large-scale distributed applications and backend services.
• Expert with Java, Kotlin to build server side technologies is required.
• A solid foundation in Data Structures, Algorithms, Object-Oriented Programming, Software Design/architecture, and core Statistics knowledge
• Experience in the close examination of data, computation of statistics, and deriving of data insights
• Proven experience designing and operating Big Data processing pipelines (Hadoop, Spark) and working with NoSQL databases or key-value stores (e.g., MongoDB, Redis).
• Hands-on experience with the end-to-end lifecycle of machine learning, including model deployment and application at scale. Experience in AI research or industrial recommendation systems is a significant plus.
• Experience with cloud services and familiarity with Large Language Models (LLMs) or prompt engineering is highly desirable.
• A passion for technical excellence, excellent communication skills, and a “can-do” attitude with a willingness to learn and master new technologies.
• Proven expertise in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, Keras.
• Strong understanding of machine learning fundamentals, algorithms, and model evaluation techniques.
• Hands-on experience with ML Ops tools and best practices.
• Proficiency in working with large scale data in hadoop and spark.
• Proficient with prediction accuracy, latency, throughput, confidence scores, and drift (data & concept)