Job Summary

Startup Inno is seeking a highly motivated and innovative AI Machine Learning Engineer with a strong focus on Predictive Maintenance to join our growing technology team. In this role, you will design, develop, and deploy machine learning models that anticipate equipment failures, optimize operational performance, and reduce downtime for industrial and enterprise systems.

You will work at the intersection of data science, engineering, and business, leveraging large-scale sensor data, IoT streams, and historical maintenance records to build intelligent, real-world solutions. This position offers the opportunity to make a tangible impact by transforming raw data into predictive insights that drive efficiency and cost savings for our clients.

Key Responsibilities

• Design and develop end-to-end machine learning pipelines for predictive maintenance use cases.

• Build, train, evaluate, and optimize ML models for anomaly detection, failure prediction, and remaining useful life (RUL) estimation.

• Process and analyze large volumes of time-series data from sensors and IoT devices.

• Collaborate with data engineers to ensure data quality, availability, and scalability.

• Deploy models into production environments using cloud-based or on-premise systems.

• Monitor model performance and continuously improve accuracy and reliability.

• Work closely with product managers and domain experts to translate business problems into AI solutions.

• Document methodologies, models, and results for internal and external stakeholders.

• Stay updated with the latest advancements in machine learning, AI, and predictive analytics.

Required Skills and Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

• Strong proficiency in Python and common ML libraries (TensorFlow, PyTorch, Scikit-learn, Keras).

• Experience with time-series analysis and predictive modeling.

• Solid understanding of machine learning algorithms, including supervised and unsupervised learning.

• Experience with data preprocessing, feature engineering, and model evaluation.

• Familiarity with cloud platforms (AWS, Azure, or GCP).

• Knowledge of SQL and experience working with structured and unstructured data.

• Strong analytical and problem-solving skills.

• Excellent communication skills with the ability to explain complex concepts clearly.

Experience

• 2–5 years of hands-on experience in machine learning or data science roles.

• Proven experience building and deploying ML models in real-world applications.

• Prior experience in industrial analytics, IoT, manufacturing, or asset management is a strong advantage.

• Experience with MLOps tools and practices is a plus.

Working Hours

• Full-time position (40 hours per week).

• Flexible working hours with the possibility of remote or hybrid work arrangements.

• Occasional collaboration across time zones depending on project requirements.

Knowledge, Skills and Abilities

• Deep understanding of statistics, probability, and linear algebra.

• Ability to work with large, complex datasets.

• Strong critical thinking and decision-making abilities.

• Capacity to work independently and in cross-functional teams.

• Passion for innovation and emerging AI technologies.

• Ability to manage multiple tasks and meet deadlines in a fast-paced environment.

Benefits

• Competitive salary and performance-based incentives.

• Flexible work arrangements (remote/hybrid options).

• Health insurance and wellness programs.

• Continuous learning and professional development opportunities.

• Access to cutting-edge AI tools and technologies.

• Collaborative, inclusive, and innovation-driven work culture.

• Career growth opportunities in a fast-scaling startup environment.

Why Join Startup Inno?

At Startup Inno, we believe in building intelligent systems that solve real-world problems. You will be part of a forward-thinking team that values creativity, experimentation, and impact. This role gives you the opportunity to work on meaningful AI projects that directly improve operational efficiency and business outcomes across industries.

We foster a culture of learning, ownership, and innovation, where your ideas are valued and your contributions truly matter.

How to Apply

Interested candidates are invited to submit their updated resume along with a brief cover letter highlighting their experience in machine learning and predictive analytics.