Machine Learning Engineer

5 days ago

Bangalore, Karnataka, India Huntingcube Recruitment Solutions Full time

We are seeking a passionate and experienced Machine Learning Engineer to join our growing team.

You will play a key role in the entire machine learning lifecycle, from problem formulation to production deployment.

You will leverage your expertise to develop, implement, and monitor machine learning models that solve real-world business Collaborate with data scientists, product managers, and engineers to identify business problems suitable for machine learning solutions.

- Formulate machine learning problems by defining success metrics, data requirements, and model evaluation strategies.

- Design, develop, and train machine learning models using various algorithms and techniques (e.g, supervised, unsupervised, deep learning).

- Pre-process, clean, and engineer features from raw data for model training.

- Evaluate model performance using appropriate metrics and identify opportunities for improvement.

- Develop and implement production-grade machine learning pipelines using tools like Airflow or MLFlow.

- Deploy and monitor machine learning models in cloud environments (e.g, AWS, Azure, GCP).

- Integrate machine learning models with backend systems and APIs for real-world applications.

- Continuously monitor model performance, identify potential biases, and perform model retraining as needed.

- Document your work effectively, including model design decisions, training processes, and evaluation results.

- Stay up-to-date with the latest advancements in machine learning algorithms, tools, and cloud platforms.

- Collaborate with the broader team to ensure seamless integration of machine learning solutions within the product or service.

Technical Skills (Required):

- B.Tech/M.Tech in Computer Science or a related discipline (e.g, Statistics, Mathematics).

- 4-6 years of industry experience with a proven track record of ownership and delivery in machine learning projects.

- Strong understanding of core machine learning concepts (supervised learning, unsupervised learning, deep learning) and basic statistics.

- Experience with popular machine learning libraries (e.g, scikit-learn, PyTorch, TensorFlow).

- Proficiency in software engineering principles and practices for building production-grade services.

- Experience with cloud platforms (AWS, Azure, GCP) for deploying and managing machine learning models (a plus).

- Experience with version control systems (e.g, Git).

- Excellent problem-solving, analytical, and critical thinking skills.

- Strong communication, collaboration, and teamwork skills.

Technical Skills (Desired):

- Experience with cloud-based application and infrastructure deployment and management tools.

- Familiarity with common machine learning components like Airflow and MLFlow.

- Knowledge of relevant cloud provider services for machine learning (e.g, AWS SageMaker, Azure Machine Learning).

- Understanding of Large Language Models (LLMs) core concepts, libraries, and application design patterns (a plus)

(ref:hirist.tech)

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