
Job Description
Responsibilities:
- Collaborate with stakeholders to understand business objectives and requirements for AI/ML projects.
- Conduct research and stay up-to-date with the latest AI/ML algorithms, techniques, and frameworks.
- Design and develop machine learning models, algorithms, and data pipelines.
- Collect, preprocess, and clean large datasets to ensure data quality and reliability.
- Train, evaluate, and optimize machine learning models using appropriate evaluation metrics.
- Implement and deploy AI/ML models into production environments.
- Monitor model performance and propose enhancements or updates as needed.
- Collaborate with software engineers to integrate AI/ML capabilities into existing software systems.
- Perform data analysis and visualization to derive actionable insights.
- Stay informed about emerging trends and advancements in the field of AI/ML and apply them to improve existing solutions.
Strong experience in Apache pyspark is must
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience of 3-5 years as an AI/ML Engineer or a similar role.
- Strong knowledge of machine learning algorithms, deep learning frameworks, and data science concepts.
- Proficiency in programming languages such as Python, Java, or C++.
- Experience with popular AI/ML libraries and frameworks, such as TensorFlow, Keras, PyTorch, or scikit-learn.
- Familiarity with cloud platforms, such as AWS, Azure, or GCP, and their AI/ML services.
- Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Experience in deploying and scaling machine learning models in production environments.
- Strong problem-solving skills and ability to work on multiple projects simultaneously.
- Excellent communication and teamwork skills.
Preferred Skills:
- Experience with natural language processing (NLP) techniques and tools.
- Familiarity with big data technologies, such as Hadoop, Spark, or Hive.
- Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
- Understanding of DevOps practices for AI/ML model deployment
-Apache ,Pyspark

About Kanerika Software
About
Since 2015, Kanerika has been helping businesses turn ideas into impactful software products. With over 75 years of collective expertise, our team brings together deep product engineering knowledge and a passion for solving complex challenges. We focus on building software that is not just functional but transformative—solutions that create lasting value for our clients.
At Kanerika, we believe great outcomes come from strong partnerships, proven experience, and creative thinking. That’s why we keep our team lean, our approach hands-on, and our commitment unwavering: to deliver products that exceed expectations every time.
Candid answers by the company
Kanerika designs and develops software products that transform business challenges into lasting value.
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