Research Scientist - Machine Learning/Artificial Intelligence

Job Title : AI/ML Engineer (Python)

Location : Gurgaon

Experience : 5+ Years and 10+ Years

Role Overview :

We are seeking highly skilled AI/ML Engineers with expertise in Python to join our team in Gurgaon. The ideal candidates will have 5+ Years or 10+ Years of experience in building and deploying AI/ML models, developing scalable solutions, and contributing to cutting-edge machine learning projects.

Key Responsibilities :

• Design, develop, and deploy robust AI/ML models and algorithms to solve real-world problems.
• Collaborate with cross-functional teams to integrate machine learning solutions into production environments.
• Implement data preprocessing, feature engineering, and model optimization techniques.
• Work with large datasets to derive insights and develop predictive models.
• Write clean, efficient, and well-documented Python code.
• Evaluate model performance and fine-tune algorithms for better accuracy and efficiency.
• Research and implement new machine learning methods and technologies.
• Develop and maintain automated pipelines for training, testing, and deploying models.
• Mentor junior engineers (for 10+ Years of experience candidates).

Key Requirements :

Educational Qualification : Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

Experience :

• For 5+ Years : Proven expertise in AI/ML development with hands-on project experience.
• For 10+ Years : Advanced expertise in AI/ML with a track record of leading complex projects and mentoring teams.

Technical Skills :

• Strong programming skills in Python.
• Expertise in machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Proficiency in data processing tools such as Pandas and NumPy.
• Experience with cloud platforms (AWS, Azure, or GCP) for deploying models.
• Knowledge of NLP, computer vision, or deep learning techniques is a plus.
• Familiarity with big data tools (e.g., Spark, Hadoop) is advantageous.

Soft Skills :

• Strong analytical and problem-solving abilities.
• Excellent communication and team collaboration skills.
• Ability to adapt to a fast-paced and dynamic environment.

Preferred Qualifications :

• Hands-on experience with MLOps tools and workflows.
• Familiarity with version control systems like Git.
• Exposure to end-to-end product lifecycle from ideation to deployment.

Benefits :

• Competitive salary and performance-based incentives.
• Opportunity to work on cutting-edge AI/ML projects.
• Collaborative and innovative work environment.
• Continuous learning and upskilling opportunities.

Responsibilities

> Selecting features, building and optimizing classifiers using machine

> learning techniques

> Data mining using state-of-the-art methods

> Extending company’s data with third party sources of information when

> needed

> Enhancing data collection procedures to include information that is

> relevant for building analytic systems

> Processing, cleansing, and verifying the integrity of data used for

> analysis

> Doing ad-hoc analysis and presenting results in a clear manner

> Creating automated anomaly detection systems and constant tracking of

> its performance

Key Skills

> Hands-on experience of analysis tools like R, Advance Python

> Must Have Knowledge of statistical techniques and machine learning

> algorithms

> Artificial Intelligence

> Understanding of Text analysis- Natural Language processing (NLP)

> Knowledge on Google Cloud Platform

> Advanced Excel, PowerPoint skills

> Advanced communication (written and oral) and strong interpersonal

> skills

> Ability to work cross-culturally

> Good to have Deep Learning

> VBA and visualization tools like Tableau, PowerBI, Qliksense, Qlikview

> will be an added advantage

We at Thena are looking for a Machine Learning Engineer with 2-4 years of industry experience to join our team. The ideal candidate will be passionate about developing and deploying ML models that drive business value and have a strong background in ML Ops.

Responsibilities:

• Develop, fine-tune, and deploy ML models for B2B customer communication and collaboration use cases.
• Collaborate with cross-functional teams to define requirements, design models, and deploy them in production.
• Optimize model performance and accuracy through experimentation, iteration, and testing.
• Build and maintain ML infrastructure and tools to support model development and deployment.
• Stay up-to-date with the latest research and best practices in ML, and share knowledge with the team.

Qualifications:

• 2-4 years of industry experience in machine learning engineering, with a focus on natural language processing (NLP) and text classification models.
• Experience with ML Ops, including deploying and managing ML models in production environments.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with Embeddings and building on top of LLMs.
• Strong problem-solving and analytical skills, with the ability to develop creative solutions to complex problems.
• Strong communication skills, with the ability to collaborate effectively with cross-functional teams.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.

Roles and Responsibilities

• Managing available resources such as hardware, data, and personnel so that deadlines are met.
• Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
• Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Defining validation framework and establish a process to ensure acceptable data quality criteria are met
• Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
• Device self-learning strategies through analysis of errors from the models
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
• Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
• Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.

Preferred Technical & Professional expertise

• Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
• At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
• In-depth knowledge of cloud analytics tools.
• Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
• Ability to evaluate hardware selection for running ML models for optimal performance
• Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
• Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
• Deep analytical thinking with excellent problem-solving abilities
• Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
• Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
• Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
• Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards