Job Description

Job Overview :

As a Machine Learning Engineer at [Netbounce Global], you will work on designing, developing, and deploying machine learning models and systems to solve complex real-world problems. You will collaborate closely with data scientists, software engineers, and product managers to build robust, scalable, and efficient ML solutions.

Key Responsibilities :

• Develop and implement machine learning models and algorithms for various applications, such as predictive analytics, natural language processing, and computer vision.
• Analyze large datasets to derive actionable insights and build data-driven solutions.
• Collaborate with cross-functional teams to integrate machine learning models into production environments.
• Optimize machine learning algorithms for speed, accuracy, and scalability.
• Conduct performance evaluations and fine-tuning of models to ensure they meet business objectives.
• Keep up to date with the latest developments in machine learning, AI, and related technologies, and integrate these innovations into the team's workflow.
• Provide mentorship and guidance to junior engineers and team members.
• Write clean, maintainable, and efficient code while following industry best practices.

Required Qualifications :

• Master’s degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
• Proven experience (0-4 years) working as a Machine Learning Engineer or in a similar role.
• Strong proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras.
• Solid understanding of machine learning concepts including supervised/unsupervised learning, deep learning, and reinforcement learning.
• Strong knowledge of algorithms, data structures, and software engineering best practices.
• Experience with data wrangling, preprocessing, and feature engineering.
• Familiarity with cloud computing platforms (AWS, GCP, Azure) for ML model deployment.
• Knowledge of SQL and experience working with large datasets.
• Experience with version control systems (e.g., Git).

Preferred Qualifications :

• Masters in Computer Science, Artificial Intelligence, or a related field.
• Experience with deploying machine learning models in a production environment.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
• Strong analytical, problem-solving, and communication skills.

Benefits :

• Competitive salary and performance-based bonuses.
• Health, dental, and vision insurance.
• 401(k) with company matching.
• Generous paid time off and holiday schedule.
• Opportunities for professional development and continuing education.
• Collaborative and dynamic work environment.

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