Sr. AI Software Engineer

2 Months ago • 9 Years + • Artificial Intelligence • Undisclosed

About the job

Job Description

Dew Software is seeking a highly skilled and experienced Sr. AI Software Engineer to join their team. You will be responsible for developing and implementing cutting-edge artificial intelligence solutions for clients. Responsibilities include designing, developing, and implementing AI models and algorithms, working with data scientists and stakeholders to understand requirements, optimizing and enhancing model performance, implementing and deploying AI models into production systems, collaborating with cross-functional teams to integrate AI capabilities, staying up-to-date with AI advancements, conducting research, and exploring new techniques and methodologies.
Must have:
  • Proficiency in Python
  • Experience with TensorFlow, PyTorch, and Keras
  • Understanding of generative models (GANs, VAEs, transformers)
  • Data pre-processing, augmentation, and handling large datasets
  • Knowledge of NLP techniques (tokenization, text generation, sentiment analysis)
  • Ability to work with large language model APIs
  • Strong foundation in software engineering principles
  • Familiarity with cloud platforms (AWS, Azure, Google Cloud)
  • Expertise in designing and optimizing prompts for AI chatbots

Description

Dew Software is seeking a highly skilled and experienced Sr. AI Software Engineer to join our team. As a Sr. AI Software Engineer, you will be responsible for developing and implementing cutting-edge artificial intelligence solutions for our clients. You will work on exciting projects in the field of machine learning, natural language processing, and computer vision. If you are passionate about AI and have a strong background in software engineering, we’d love to hear from you.


Responsibilities

  • Design, develop, and implement AI models and algorithms to solve complex business problems.
  • Work closely with data scientists and stakeholders to understand requirements and translate them into technical solutions.
  • Optimize and enhance the performance of AI models using techniques such as hyperparameter tuning and feature engineering.
  • Implement and deploy AI models into production systems.
  • Collaborate with cross-functional teams to integrate AI capabilities into existing software systems.
  • Stay up to date with the latest advancements in AI technologies and frameworks.
  • Conduct research and experiments to explore new AI techniques and methodologies.

Requirements

Programming Languages: Proficiency in languages like Python.

 Machine Learning Frameworks: Experience with frameworks such as TensorFlow, PyTorch, and Keras.

 Generative Models: Understanding of generative models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models (e.g., GPT, BERT).

 Data Handling: Skills in data pre-processing, data augmentation, and handling large datasets.

 NLP (Natural Language Processing): Knowledge of NLP techniques, including tokenization, text generation, and sentiment analysis.

 API Integration: Ability to work with large language model APIs and integrate them into applications.

 Software Development: Strong foundation in software engineering principles, including version control, system integration, and DevOps practices.

 Cloud Services: Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying AI models.

 Prompt Engineering: Expertise in designing and optimizing prompts for AI chatbots and other generative AI applications.

Benefits

Qualifications: 1. Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field. 2. At least 9+ years of practical experience in backend development, with a strong command of one or more programming languages like Python, Go or JAVA. 3. Proven experience in designing and developing scalable backend systems for high-traffic applications. 4. Familiarity with cloud-based infrastructures (e.g. AWS, Google Cloud) and container technologies (e.g. Docker, Kubernetes). 5. Solid understanding of database systems and data modeling, as well as proficiency in SQL and NoSQL databases. 6. Experience with RESTful API design and implementation, and understanding of microservices architecture. 7. Knowledge of security best practices and data protection measures for backend systems. 8. Strong problem-solving skills and the ability to troubleshoot complex technical issues. 9. Excellent team player with good communication and collaboration skills.

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