
Software Test Engineer
2 weeks ago
Summary
We are seeking a talented Software Test Engineer to join our engineering team and drive the design, development, and deployment of AI-powered solutions. This role is ideal for professionals passionate about artificial intelligence, machine learning, and software engineering who want to make a tangible impact on real-world applications.
As a Software Test Engineer, you will collaborate with engineers, data scientists, and product managers to build, optimize, and scale AI models and systems. You will work with cutting-edge tools and frameworks while applying your expertise in algorithms, data processing, and system integration to deliver high-performance AI solutions.
Key Responsibilities
- Design, develop, test, and deploy AI/ML models and applications.
- Build data pipelines for preprocessing, cleaning, and transforming large datasets.
- Train, evaluate, and fine-tune machine learning models for production use.
- Integrate AI models into applications and production systems.
- Research and implement new AI frameworks, tools, and methodologies to enhance capabilities.
- Debug, optimize, and scale algorithms to improve system performance.
- Collaborate with cross-functional teams (data science, product, engineering) to deliver end-to-end AI solutions.
- Contribute to technical documentation, code reviews, and best practices.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Strong programming skills in Python, Java, or C++.
- Solid understanding of machine learning concepts (classification, regression, NLP, computer vision, deep learning).
- Hands-on experience with frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Proficiency in algorithms, data structures, and object-oriented programming.
- Experience building and deploying AI applications in real-world environments.
- Strong analytical, problem-solving, and debugging skills.
Preferred Qualifications
- Experience with large-scale data pipelines and distributed systems.
- Familiarity with cloud platforms (AWS, Azure, or GCP).
- Knowledge of APIs, microservices, and containerization (Docker, Kubernetes).
- Exposure to MLOps practices and continuous integration/continuous deployment (CI/CD).
- Strong interest in applied AI and innovation in emerging technologies.
Apply Now
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