Machine Learning Specialist / Custom Software Engineer

Custom Software Engineer

Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Machine Learning (ML)
Good to have skills : Python (Programming Language), AWS AI Services, AWS Architecture
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary
As a Machine Learning Specialist / Application Developer, you will design, build, and optimize ML-driven applications to meet complex business and product requirements. Your role involves collaborating with cross-functional teams to translate business needs into scalable ML solutions, implementing advanced algorithms, and integrating models into production systems. You will be responsible for driving innovation, ensuring model reliability, and contributing to strategic decisions that impact multiple teams and project outcomes. A typical day includes problem-solving, model experimentation, performance tuning, and guiding teams with your expertise in Machine Learning and application development.

Roles & Responsibilities
Serve as a Subject Matter Expert (SME) in Machine Learning, guiding teams on best practices, model design, and solution development.
Lead and collaborate with teams to ensure high-quality ML solution delivery.
Provide technical leadership and accountability for decisions impacting multiple project teams.
Engage with product, engineering, and data teams to influence key architectural and algorithmic choices.
Deliver end-to-end ML solutions, including data preparation, model development, evaluation, and deployment.
Provide cross-team solutions for recurring problems, ensuring consistency and scalability across systems.
Conduct knowledge-sharing sessions, code reviews, and mentoring to enhance team capabilities.
Monitor project progress, model performance, and ensure alignment with business expectations and timelines.
Contribute to continuous improvement of ML frameworks, pipelines, and development standards.

Professional & Technical Skills
Must-Have Skills:
Strong proficiency in Machine Learning, including algorithm selection, feature engineering, and optimization.
Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.
Ability to analyze, interpret, and model complex datasets.
Experience integrating models into applications using frameworks/tools such as Python, Flask/FastAPI, Spark, or cloud ML services.
Solid understanding of the software development life cycle (SDLC) and MLOps practices.
Additional Technical Skills:
Knowledge of data processing pipelines, model deployment, and monitoring.
Familiarity with version control (Git), CI/CD, and collaborative development workflows.
Strong understanding of model validation, A/B testing, and performance tuning.
Ability to solve ambiguous technical problems and design scalable ML solutions.

Additional Information
Experience working in Agile environments or multi-disciplinary teams is a plus.
Exposure to cloud platforms (AWS, GCP, Azure) and ML services is an added advantage.
Strong communication and stakeholder management skills.
Ability to work independently, lead initiatives, and drive innovation across teams.