AI Engineer

At DevSavant, we are a trusted technology partner delivering cutting-edge solutions across Software Development, Data Engineering, AI/Machine Learning, Cloud Services, Automation Testing, and UI/UX Design. We are driven by a commitment to excellence and measurable results. Our team is our greatest asset—we foster a culture of growth, collaboration, and well-being. Join us and thrive in an environment designed for success.

Our client offers a cloud-based, AI-powered platform that helps accounting, tax, audit, and bookkeeping professionals streamline operations and enhance productivity through an all-in-one solution.

We are looking for an experienced AI Engineer (3–5 years) to help design and implement intelligent features across the platform.

Job Overview:
The AI Engineer will be responsible for designing, developing, and deploying AI-driven solutions to enhance the platform. You will work closely with cross-functional teams, including product managers, data scientists, and software engineers, to implement machine learning models, optimize AI systems, and integrate these capabilities into our cloud-based platform. You will have the opportunity to contribute to meaningful AI innovations that improve workflows, automate processes, and deliver measurable value to our customers.

This is a remote work-from-home position with occasional travel required for team meetings, conferences, and client engagements.

Key Responsibilities:

• AI Model Development:
  Design, develop, and implement machine learning models and AI algorithms to solve business problems within the practice management space. Work on enhancing features such as document management, data automation, and predictive analytics.

• Data Preprocessing and Feature Engineering:
  Perform data preprocessing tasks such as cleaning, transformation, and feature engineering to prepare datasets for model training. Ensure data quality and integrity to support AI model development.

• AI Model Training and Optimization:
  Train machine learning models on large datasets, tune hyperparameters, and optimize models to achieve high accuracy and efficiency. Evaluate and refine AI models to meet performance benchmarks.

• AI Integration:
  Collaborate with software engineers to integrate machine learning models and AI systems into the broader platform. Ensure smooth deployment and scaling of AI solutions within a cloud-based environment.

• Collaboration with Cross-functional Teams:
  Work closely with data scientists, product managers, and software engineers to align AI solutions with customer needs and business goals. Contribute to product features by providing insights and expertise on AI technologies.

• Continuous Learning and Innovation:
  Stay up to date with the latest AI trends, tools, and technologies. Implement cutting-edge solutions and participate in AI research to improve the quality and impact of AI features.

• Performance Monitoring and Metrics:
  Track the performance of AI models and AI-powered features after deployment. Use metrics to assess effectiveness and identify areas for continuous improvement.

Qualifications:

• Experience:
  3–5 years of experience in AI, machine learning, or data science, with a strong track record of developing and deploying machine learning models. Experience working with cloud-based platforms (AWS, Google Cloud, etc.) is a plus.

• Technical Expertise:
  Proficiency in machine learning algorithms, deep learning, and natural language processing (NLP). Experience with popular AI frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras.

• Programming Skills:
  Strong coding skills in Python (or other relevant programming languages) and familiarity with data manipulation libraries such as NumPy, Pandas, and Matplotlib. Knowledge of SQL and experience working with databases is a plus.

• Data Handling:
  Strong understanding of data preprocessing, feature engineering, and model validation techniques. Ability to work with large datasets and implement efficient data pipelines.

• Cloud & AI Integration:
  Experience with deploying and integrating machine learning models into cloud platforms (AWS, Google Cloud, Azure) and knowledge of containerization tools like Docker is beneficial.

• Problem-Solving Skills:
  Strong analytical skills and a problem-solving mindset. Ability to approach complex challenges with creative and efficient AI-driven solutions.

• Education:
  A Bachelor's degree in Computer Science, Data Science, Engineering, or a related field is required. A Master’s degree or certification in AI/ML is a plus.