Location: Permanent WFH/Remote

Type : Fulltime

About the Role:

We are looking for a Platform Engineer who thrives on designing, deploying, and managing complex solutions across multiple cloud platforms. This role is perfect for someone who can navigate AWS, Azure, GCP, or other cloud environments with ease and has a knack for making systems understandable and explainable to both technical and non-technical audiences. If you enjoy solving complex problems, building robust infrastructures, and continuously improving platform performance, you’ll fit right in.

What You’ll Be Doing:

Designing and Deploying Cloud Solutions

• Architect and implement cloud-based platforms and solutions that meet business requirements.
• Work across multiple cloud environments to deploy scalable and secure systems.
• Develop and maintain infrastructure as code using tools such as Terraform, CloudFormation, or similar.
• Ensure that complex systems are built with transparency and are explainable to all stakeholders.

Optimizing Platform Performance

• Monitor and analyze system performance, troubleshooting issues as they arise.
• Implement automation and CI/CD pipelines to streamline deployment and operations.
• Work closely with engineering teams to integrate systems and optimize workflows.

Ensuring Explainability and Transparency

• Develop documentation and visualizations that clearly articulate the architecture and functionality of deployed systems.
• Collaborate with cross-functional teams to demystify technical details for business and technical audiences alike.
• Maintain a focus on making systems auditable and compliant with relevant standards.

Collaborating and Innovating

• Act as a bridge between technical teams and business stakeholders, ensuring clear communication of platform capabilities and limitations.
• Stay current with the latest cloud technologies, best practices, and industry trends.
• Propose and implement improvements to existing systems based on feedback and performance data.

What We’re Looking For:

Cloud and Infrastructure Expertise

• Proven experience navigating and deploying solutions across multiple cloud platforms (AWS, Azure, GCP, etc.).
• Strong knowledge of infrastructure as code, containerization, and orchestration tools.
• Familiarity with CI/CD practices and automation tools is essential.

Technical Problem-Solving Skills

• Ability to diagnose and resolve complex issues in distributed systems.
• A knack for simplifying technical concepts, making them understandable for diverse audiences.
• Experience with monitoring tools and performance optimization strategies.

Communication and Documentation Skills

• Excellent written and verbal communication skills.
• Ability to create clear, comprehensive documentation and visual representations of system architecture.
• Comfortable explaining technical details in layman’s terms.

Learning Mindset and Collaborative Spirit

• Curiosity and a drive to stay updated with emerging cloud technologies and best practices.
• Willingness to learn and adapt in a fast-paced environment.
• Team-oriented with a proactive approach to solving challenges.

Experience Needed:

• 5+ years of experience in platform engineering, cloud infrastructure, or a related field.
• Demonstrated experience in deploying and managing solutions on multiple cloud platforms.
• A solid track record of working in collaborative, cross-functional teams to deliver complex projects.

Send us your resume to [email protected]

Location: Permanent WFH/Remote

Type : Fulltime

About the Role:

We are looking for a Senior Machine Learning Engineer who can take complex machine learning models and make them work in real-world production environments. This role is ideal for someone who not only has deep expertise in machine learning but also understands the challenges of deployment, scalability, and performance optimization across different platforms.

Beyond technical skills, we need someone who can lead a team of MLEs, design end-to-end ML solutions, and effectively communicate technical concepts to both engineers and business stakeholders. If you enjoy solving hard problems, working with cutting-edge ML technologies, and taking ownership of projects from idea to deployment, this role is for you.

What You’ll Be Doing:

Building and Deploying ML Models

• Design, build, optimize, deploy and monitor machine learning models for production use cases.
• Ensure scalability, reliability, and efficiency of ML pipelines across cloud and on-prem environments.
• Work with data engineers to design data pipelines that feed into ML models.
• Optimize model performance, ensuring low latency and high accuracy.

Leading and Architecting ML Solutions

• Lead a team of ML Engineers, providing technical mentorship and guidance.
• Architect ML solutions that integrate seamlessly with business applications.
• Ensure models are explainable, auditable, and aligned with business goals.
• Drive best practices in MLOps, CI/CD, and model monitoring.

Collaborating and Communicating

• Work closely with business stakeholders to understand problem statements and define ML-driven solutions.
• Collaborate with software engineers, data engineers, platform engineers and product managers to integrate ML models into production systems.
• Present technical concepts to non-technical stakeholders in an easy-to-understand manner.

What We’re Looking For:

Machine Learning Expertise

• Deep understanding of supervised and unsupervised learning, deep learning, and NLP techniques, and large language models (LLMs).
• Experience in training, fine-tuning, and deploying ML and LLM models at scale.
• Proficiency in ML frameworks such as TensorFlow, PyTorch, Scikit-learn etc.

Production and Cloud Deployment 

• Hands-on experience deploying models to AWS, GCP, or Azure.
• Understanding of MLOps, including CI/CD for ML models, model monitoring, and retraining pipelines.
• Experience working with Docker, Kubernetes, or serverless architectures is a plus.

Data Handling 

• Strong programming skills in Python.
• Proficiency in SQL and working with large-scale datasets.
• Familiarity with distributed computing frameworks like Spark or Dask is a plus.

Leadership and Communication

• Ability to lead and mentor a team of ML Engineers and collaborate effectively across functions.
• Strong communication skills to explain technical concepts to business teams.
• Passion for staying updated with the latest advancements in ML and AI.

Experience Needed:

• 6+ years of experience in machine learning engineering or related roles.
• Experience in deploying and managing ML and LLM models in production.
• Proven track record of working in cross-functional teams and leading ML projects.

Send us your resume to [email protected]

Location: Permanent WFH/Remote

Type : Fulltime

About the Role:

We are looking for a Junior Machine Learning Engineer who is eager to grow and contribute to real-world ML projects. In this role, you’ll work closely with experienced engineers and data scientists to develop, test, and deploy machine learning models. This is a fantastic opportunity for someone who is enthusiastic about machine learning, enjoys hands-on learning, and is ready to take on challenges in a collaborative environment.

What You’ll Be Doing:

Supporting Model Development

• Assist in designing and building machine learning models for various applications.
• Help with data preprocessing, feature engineering, and model evaluation.
• Collaborate on developing prototypes and iterating on model performance.

Deployment and Maintenance

• Work with senior team members to deploy ML models into production environments.
• Support the creation and maintenance of automated ML pipelines.
• Monitor model performance and assist in troubleshooting issues as they arise.

Collaborating and Learning

• Participate in team meetings and contribute ideas to improve existing models and processes.
• Collaborate with cross-functional teams to understand business problems and how AI/ML can provide solutions.
• Stay updated on the latest trends in machine learning and apply new techniques under guidance.

Documentation and Best Practices

• Help document processes, experiments, and results to maintain clear records of project developments.
• Follow best practices for coding, testing, and model versioning to ensure high-quality work.

What We’re Looking For:

Technical Skills

• Knowledge of machine learning, deep learning and LLM concepts.
• Familiarity with at least one ML framework such as TensorFlow, PyTorch, or Scikit-learn.
• Hands-on knowledge of Python, and a willingness to learn more advanced tools.

Analytical and Problem-Solving Skills

• Ability to approach problems methodically and break them down into manageable tasks.
• A keen interest in experimenting with new ideas and learning from both successes and challenges.

Communication and Collaboration

• Good written and verbal communication skills, with the ability to clearly explain technical details to teammates and clients.
• A team player attitude, with a desire to work in a collaborative, supportive environment.

Learning Mindset

• Curiosity and a drive to continuously learn and grow in the field of machine learning.
• Openness to feedback and a proactive approach to expanding your skillset.

Experience Needed:

• 3+ years of experience in machine learning, data science, or a related field.
• Demonstrated real-world problem-solving capability in machine learning through various production grade projects/solutions.

Send us your resume to [email protected]