Machine Learning Engineer

Education:

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related certifications or experience in NLP & CV.

Years of Experience:

Minimum 2 years of experience in Deep Learning, NLP,CV, MLOps and its related technologies.

Responsibilities:

- Design, develop, and deploy state-of-the-art NLP and CV models and algorithm

- Collaborate with cross-functional teams to understand requirements and develop customised NLP & CV solutions and have experience in building the python backend using Flask / Django.

- Database integration preferably using MongoDB or any other vector databases.

- Maintain and improve the performance, accuracy, and efficiency of existing AI/ML models and their deployment on Cloud platforms (AWS) and monitor their performance using MLOps tools such as MLFlow, DVC.

- Experience in building End to End data pipelines

- Stay updated with emerging AI/ML technologies, LLM's ,RAG

- Conduct regular performance evaluations of AI/ML models using production grade MLOps solutions.

- Troubleshoot and resolve any issues arising from the implementation of NLP & CV models.

- Develop and monitor the code that runs in production environments using MLOps practices.

Requirements:

- Strong experience with Deep learning and NLP frameworks such as TensorFlow or other open-source machine learning frameworks.

- Experience of using both tensorflow and pytorch frameworks

- Proficient in programming languages, such as Python or Java, and experience with AI/ML libraries.

- Familiarity with the integration of APIs, such as REST API, OpenAI API, for implementing advanced AI-driven features.

- Solid understanding of Machine learning and Deep learning algorithms, concepts, and best practices in a production environment using MLOps.

- Experience with big data technologies, such as Hadoop and Spark, is a plus.

- Strong problem-solving skills.

- Excellent communication and teamwork skills, with the ability to collaborate effectively with team members from various disciplines.

- Eagerness to learn and adapt to new technologies and industry trends.