Apply on Kit Job: kitjob.in/job/4qxqre

As a Machine Learning Engineer (MLE) at our company, you will be responsible for applying your strong software engineering and machine learning expertise to industrialize predictive and prescriptive solutions across big datasets. You will handle both streaming and non-streaming analytics use cases while having a deep understanding of analytics and data science. Your main tasks will involve engineering performant and robust code and applying best-in-class development frameworks.

Key Responsibilities

- Utilize your expertise in software engineering and machine learning to industrialize predictive and prescriptive solutions - Handle both streaming and non-streaming analytics use cases - Engineer performant and robust code - Apply best-in-class development frameworks Qualifications Required:
- BSc/MSc in computer science, mathematics, or related technical discipline - 1-4 years of experience in software engineering with exposure to statistical and/or data science role (5-10 years for Senior ML Engineer) - Deep knowledge and proven experience with optimizing machine learning models in a production context - Experience with Python or Scala is required.

Background in programming in C, C++, Java is beneficial - Exposure to both streaming and non-streaming analytics - Experience with SQL, Spark, Pandas, Numpy, SciPy, Statsmodels, Stan, pymc3, Caret, Scikit-learn, Keras, TensorFlow, Pytorch, Databricks is beneficial - Experience working with large datasets, simulation/optimization, and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.) - Refactor prototypes of predictive models into highly performant, production-ready solutions - Work closely with Data Engineers and Data Scientists to create analytical variables, metrics,



and models - Solve difficult engineering and machine learning problems and produce high-quality code in collaboration with data scientists - Choose and use the right analytical libraries, programming languages, and frameworks for each task - Contribute to building client capabilities by coaching team members on data science methodologies and approaches - Contribute to best coding and engineering practices across AI projects - Build/refactor/develop code into reusable libraries, APIs, and tools - Build a sense of trust and rapport to create a comfortable and effective workplace in a collaborative environment - Thrive in a fun, fast-paced, startup-like environment - Open-minded to new approaches and learning We are excited to have you join our team and look forward to hearing from you at the earliest! As a Machine Learning Engineer (MLE) at our company, you will be responsible for applying your strong software engineering and machine learning expertise to industrialize predictive and prescriptive solutions across big datasets. You will handle both streaming and non-streaming analytics use cases while having a deep understanding of analytics and data science.

Your main tasks will involve engineering performant and robust code and applying best-in-class development frameworks.

Key Responsibilities





- Utilize your expertise in software engineering and machine learning to industrialize predictive and prescriptive solutions - Handle both streaming and non-streaming analytics use cases - Engineer performant and robust code - Apply best-in-class development frameworks Qualifications Required:
- BSc/MSc in computer science, mathematics, or related technical discipline - 1-4 years of experience in software engineering with exposure to statistical and/or data science role (5-10 years for Senior ML Engineer) - Deep knowledge and proven experience with optimizing machine learning models in a production context - Experience with Python or Scala is required.

Background in programming in C, C++, Java is beneficial - Exposure to both streaming and non-streaming analytics - Experience with SQL, Spark, Pandas, Numpy, SciPy, Statsmodels, Stan, pymc3, Caret, Scikit-learn, Keras, TensorFlow, Pytorch, Databricks is beneficial - Experience working with large datasets, simulation/optimization, and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.) - Refactor prototypes of predictive models into highly performant, production-ready solutions - Work closely with Data Engineers and Data Scientists to create analytical variables, metrics, and models - Solve difficult engineering and machine learning problems and produce high-quality code in collaboration with data scientists - Choose and use the right analytical libraries, programming languages, and frameworks for each task - Contribute to building client capabilities by coaching team members on data science methodologies and approaches - Contribute to best coding and engineering practices across AI projects - Build/refactor/develop code into reusable libraries, APIs, and tools - Build a sense of trust and rapport to create a comfortable and effective workplace in a collaborative setting - Thrive in a fun,

Apply on Kit Job: kitjob.in/job/4qxqre

📌 Machine Learning Engineer Data Science (India)
🏢 TWO95 International
📍 India