Machine Learning Jobs in Nepal

Job Description:

We are looking for an experienced AI Machine Language Engineer to join our team and help us build the next generation of AI-powered products. The ideal candidate will have a strong understanding of machine learning algorithms and techniques, as well as experience with data science and software engineering.

Responsibilities:

• Collaborate with stakeholders to understand business requirements and identify opportunities for applying machine learning and AI techniques.
• Collect, preprocess, and analyze large datasets to extract relevant insights, identify patterns and develop predictive models.
• Design, develop, and implement machine learning algorithms and models using Python
• Conduct experiments and tests to evaluate and optimize the performance of machine learning models
• Work with software engineers and data engineers to integrate models into production systems and ensure scalability and efficiency.
• Stay up-to-date on the latest advances in AI and machine learning
• Present findings and insights to both technical and non-technical stakeholders in a clear and concise manner.

Required Knowledge, Skills, and Abilities:

• Strong programming skills in Python, R, or Java
• Experience with data science tools and frameworks
• Experience with cloud computing platforms
• Excellent problem-solving and analytical skills
• Ability to work independently and as part of a team

Education + Experience:

• Master's degree in computer science, data science, or a related field
• 3+ years of experience in machine learning
• Prior experience in implementing machine learning solutions in a production environment is a plus.

Apply Instruction:

Interested candidates fulfilling the mentioned criteria are encouraged to Apply using the Easy Apply Button below. Registered candidates may also apply using Apply Now Button. 

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Job Description:

• Develop and implement AI models and algorithms: Design, develop, and deploy machine learning and deep learning models using OpenAI technologies and frameworks. This includes data preprocessing, feature engineering, model training, and evaluation.
• Collaborate with cross-functional teams: Work closely with data scientists, software engineers, and domain experts to understand project requirements, gather data, and develop AI solutions that meet specific business needs.
• Conduct research and stay updated on AI advancements: Keep abreast of the latest advancements and trends in the field of AI, particularly in natural language processing, computer vision, and reinforcement learning. Apply new techniques and approaches to improve model performance and efficiency.
• Data analysis and preprocessing: Analyze and preprocess large volumes of data to ensure its quality, completeness, and suitability for training AI models. Implement data cleaning, transformation, and feature extraction techniques to optimize model performance. Model training and evaluation: Train AI models using appropriate algorithms and frameworks, fine-tuning parameters, and conducting experiments to improve model accuracy and performance. Evaluate models using appropriate evaluation metrics and statistical techniques.
• Model deployment and integration: Deploy trained AI models into production systems and integrate them into existing software applications or platforms. Ensure scalability, efficiency, and reliability of the deployed models.
• Performance optimization and troubleshooting: Identify bottlenecks, optimize AI models for improved performance, and resolve any issues or bugs that arise during model deployment or integration.
• Documentation and knowledge sharing: Document AI model development processes, methodologies, and outcomes. Share knowledge and insights with team members and stakeholders through technical documentation, presentations, and training sessions.
• Maintain code quality and best practices: Follow coding standards, best practices, and version control processes to ensure code quality, maintainability, and collaboration within the development team.
• Collaborate with OpenAI tools and platforms: Leverage OpenAI tools, libraries, and platforms effectively to accelerate AI model development and deployment. Stay updated on OpenAI's latest offerings and provide feedback to improve the tools and platforms.

Required Knowledge, Skills, and Abilities:

• Strong experience working with a variety of relational SQL and NoSQL databases.
• Strong experience working with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with at least one cloud provider solution (AWS, GCP, Azure).
• Strong experience with object-oriented/object function scripting languages: Python, Java, C++, etc.
• Solid understanding of Machine Learning / Deep Learning and the existing frameworks such as Tensorflow and PyTorch.
• Ability to work in a Linux environment.
• Industry experience building innovative end-to-end Machine Learning systems.
• Ability to quickly prototype ideas and solve complex problems by adapting creative approaches.
• Experience working with distributed systems, service-oriented architectures and designing APIs.
• Strong knowledge of data pipeline and workflow management tools.
• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation.
• Relevant working experience with Docker and Kubernetes will be a big plus.

Education + Experience:

• University or advanced degree in engineering, computer science, mathematics, or a related field.
• 7+ years experience developing and deploying machine learning systems into production.

Apply Instruction:

Interested candidates fulfilling the mentioned criteria are encouraged to Apply using the Easy Apply Button below. Registered candidates may also apply using Apply Now Button.

Apply Now