Machine Learning Engineer

As a Machine Learning Engineer you will build complex data processing pipelines, design and implement machine learning algorithms. You will help envision our machine learning strategy at scale and help build the future of Education Science. As a member of our data science and machine learning team, you will be interacting with multi-functional teams for data preparation and apply machine learning/data mining algorithms in efficient workflows to process large-scale data.

This Machine learning role will be responsible for delivering projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment. You will also perform ad-hoc statistical and data science analyses where required.

Key responsibilities:

• Design and prototype algorithms that run on cloud based big data environments.
• Develop feature specifications and performance metrics to capture requirements.
• Assemble representative data sets and use them to train and test new algorithms.
• Document designs and report results to product management on a regular basis.
• Identify opportunities for new algorithms and hardware improvements for future products.
• Develop and maintain data infrastructure systems that power statistical and machine learning models on large-scale datasets.
• Own data quality throughout all data lifecycles, including acquisition, cleaning, processing, and validation.
• Build platforms to facilitate the rapid iteration of machine learning and optimization algorithms.
• Work closely with Data science and Data engineering teams.
• Identify new ideas to build and evolve Machine Learning solutions, develop new features and benchmark possible solutions.
• Understand algorithms (be able to tweak them when needed) as well as infrastructure that enables fast iterations.
• Experienced user of libraries such as scikit-learn, scipy, R, NetworkX, Spacy, and NLTK.
• Knowledge in Spark, MongoDB, Vector Databases, Kafka, NoSQL databases is a plus.
• Ability to meaningfully present results of analyses in a clear and impactful manner.

Qualifications and Experience:

• 3+ years of experience in Machine Learning, NLP, and Deep Learning.
• Hands-on experience with Python (able to write reliable, extensible & production code) and building conversational agents with Langchain/LlamaIndex.
• Experience in working on datasets related to industry verticals and integrating external data sources with LLMs (RAG) - Education sector preferred.
• Working experience of deep learning, transformer architecture and Large Language Models (LLMs) and experience with any of the frameworks like Torch, Caffe, MXNet, TensorFlow.
• Hands-on experience in building conversational agents with Langchain/LlamaIndex, LLMs from providers like OpenAI, Anthropic, Google etc.
• Experience with various prompt engineering techniques including chain-of-thought (CoT) prompting, self-consistency, general knowledge prompting, and ReAct.
• Proficiency in development of APIs with FastAPI/Flask.
• Experience in MLOps, productionizing and monitoring machine learning models and LLMs and applying robust system designs and software design patterns.
• Demonstrate creativity and persistence in designing and refining prompts to achieve optimal results from LLMs.
• Experienced in integrating external data sources with LLMs and CI/CD tools such as Github Actions.