Job Role - Deep Learning Consultant

Experience - 2+ Years

Location - Bangalore (Hybrid)

Tech Stacks - SQL, AWS Redshift, Python, ML, Deep Learning (Pytorch/Tensorflow)

Job Description:

We are seeking a highly skilled and motivated Deep Learning Consultant to join our team. This role requires hands-on experience in building and deploying deep learning models, proficiency in core Machine Learning (ML) principles, and advanced projects. The ideal candidate should also be experienced in using AWS cloud services for machine learning workflows and possess 2-3 years of industry experience working on real-world deep learning problems.

Key Responsibilities:

• Design, develop, and implement deep learning models for various business applications, leveraging state-of-the-art techniques in computer vision, natural language processing, or other domains.

• Apply core machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) to solve complex business problems.

• Lead advanced machine learning projects, collaborating with cross-functional teams, from data preprocessing to model deployment.

• Evaluate model performance and improve model accuracy through hyperparameter tuning, feature engineering, and other optimization techniques.

• Deploy, scale, and manage machine learning models on AWS cloud services such as Amazon SageMaker, EC2, Lambda, and S3.

• Collaborate with data engineers and data scientists to ensure smooth integration of ML models into production systems.

• Stay up to date with the latest research and trends in deep learning and machine learning, applying cutting-edge techniques to business challenges.

• Provide technical mentorship and guidance to junior team members in deep learning and ML best practices.

Required Qualifications:

• 2-3 years of hands-on experience in developing and deploying deep learning models.

• Strong experience in core ML algorithms and frameworks such as TensorFlow, PyTorch, Keras, etc.

• Proven track record of delivering advanced machine learning projects from concept to deployment.

• Experience in using AWS cloud services for machine learning workflows (e.g., Amazon SageMaker, EC2, Lambda, S3, etc.).

• Experience in data preprocessing, feature engineering, and model optimization.

• Strong programming skills in Python (or other relevant languages) and experience with libraries like NumPy, pandas, etc.

• Excellent problem-solving skills with a keen attention to detail.

• Ability to work independently and in a collaborative environment with cross-functional teams.

Preferred Qualifications:

• Experience in handling large-scale datasets and model training on distributed systems.

• Familiarity with ML Ops and deploying models in a production environment.

• AWS Certification in Machine Learning or Data Science.

• Knowledge of DevOps practices for ML, such as continuous integration/continuous delivery (CI/CD) pipelines.