Machine Learning Engineer - 4+ years

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Job Title: Machine Learning Engineer

Location:

Experience:

Job Summary

Machine Learning Engineer / Senior Machine Learning Engineer

Key Responsibilities

• Design and develop machine learning and deep learning algorithms in collaboration with cross-functional teams, including data scientists and business stakeholders.
• Translate complex client problems into mathematical models and identify the most suitable AI/ML approach.
• Build data pipelines and automated classification systems using advanced ML/AI models.
• Conduct data mining and apply supervised/unsupervised learning to extract meaningful insights.
• Perform Exploratory Data Analysis (EDA), hypothesis generation, and pattern recognition from structured and unstructured datasets.
• Develop and implement Natural Language Processing (NLP) techniques for sentiment analysis, text classification, entity recognition, etc.
• Extend and customize ML libraries/frameworks like PyTorch, TensorFlow, and Scikit-learn.
• Visualize and communicate analytical findings using tools such as Tableau, Matplotlib, ggplot, etc.
• Develop and integrate APIs to deploy ML solutions on cloud-based platforms (AWS, Azure, GCP).
• Provide technical documentation and support for product development, business proposals, and client presentations.
• Stay updated with the latest trends in AI/ML and contribute to innovation-driven projects.

Required Skills & Qualifications

• Education:

  B.Tech/BE or M.Tech/MS in Computer Science, Computer Engineering, or related field.
• Solid understanding of data structures, algorithms, probability, and statistical methods.
• Proficiency in Python, R, or Java for building ML models.
• Hands-on experience with ML/DL frameworks such as PyTorch, Keras, TensorFlow, and libraries like Scikit-learn, SpaCy, NLTK, etc.
• Experience with cloud services (PaaS/SaaS), RESTful APIs, and microservices architecture.
• Strong grasp of NLP, predictive analytics, and deep learning algorithms.
• Familiarity with big data technologies like Hadoop, Spark, Hive, Kafka, and NoSQL databases is a plus.
• Expertise in building and deploying scalable AI/ML models in production environments.
• Ability to work independently in an agile team setup and handle multiple priorities simultaneously.
• Exceptional analytical, problem-solving, and communication skills.
• Strong portfolio or examples of applied ML use cases in real-world applications.

Why Join Us?

• Opportunity to work at the forefront of AI innovation and solve real-world challenges.
• Be part of a lean, fast-paced, and high-impact team driving AI solutions across industries.
• Flexible remote working culture with autonomy and ownership.
• Competitive compensation, growth opportunities, and access to cutting-edge technology.
• Embrace our culture of

  Learning, Engaging, Achieving, and Pioneering (LEAP)

  in every project you touch.