If your answer is YES, please read on.

Astha IT produces solutions for globally prominent names like Transcom Group, Apex, ACI, Banglalink, Government of Bangladesh, University of Hawaii, MIT, SaaS Ventures, Meriton Australia (a Fortune-500 company), and the United States Department of Defense (DoD).

We are seeking a skilled and experienced Machine Learning Engineer with a strong background in AWS SageMaker, Databricks, and Apache Spark, along with expertise in CI/CD using GitHub Actions and MLOps.

Our team members work with speed and efficiency to deliver the highest quality of work. We are looking for someone who is passionate about their client's business and ready to work on exciting projects with Fortune 500 companies and Silicon Valley startups, with great rates and zero hassles. If you are looking for a place to advance your career, enhance your skill set, and build connections around the globe, Astha IT is right for you.

Position: Full-time

Vacancy: 1

Responsibilities:

Design, develop, and deploy scalable machine learning models using AWS SageMaker, Databricks, and Apache Spark.
Implement and maintain CI/CD pipelines using GitHub Actions for the automation of ML model deployment, scaling, and monitoring.
Develop and apply MLOps practices using MLflow to ensure robust model lifecycle management, including continuous integration, continuous delivery, and continuous monitoring.
Manage and optimize job clusters on Databricks to ensure efficient use of resources and cost-effective scaling.
Develop and implement strategies for cost optimization across AWS SageMaker and Databricks, ensuring that machine learning operations are both scalable and economically sustainable.
Develop and maintain data pipelines for feature engineering, model training, and model deployment.
Optimize ML models for performance, scalability, and cost-efficiency on AWS, Databricks, and Spark.
Conduct experiments, tune hyperparameters, and assess model performance using cross-validation and other techniques.
Work with stakeholders to translate business requirements into technical solutions, ensuring alignment with overall business strategy.
Stay updated with the latest trends and advancements in machine learning, cloud computing, CI/CD, and MLOps.

Required Qualifications:

Proven experience with AWS SageMaker, Databricks, and Apache Spark.
Hands-on experience in building and maintaining CI/CD pipelines using GitHub Actions.
Proven track record in building, deploying, and managing machine learning models in production environments.
Strong programming skills in Python and familiarity with ML libraries such as TensorFlow, PyTorch, or Scikit-Learn.
Experience with data preprocessing, feature engineering, and model evaluation.
Familiarity with MLflow for model tracking and lifecycle management.
Experience with managing job clusters and optimizing costs on Databricks.
Familiarity with version control systems (e.g., Git) and CI/CD pipelines for ML (e.g., MLflow, Jenkins).
Experience with cloud infrastructure, including AWS (EC2, S3, Lambda) and Databricks.

Preferred Qualifications:

AWS ML and/or Databricks Certification.
Experience with containerization and orchestration tools like Docker and Kubernetes.
Understanding of data warehousing solutions like Amazon Redshift or Snowflake.
Familiarity with other ML platforms and tools such as Google AI Platform, Azure ML, etc.
Experience with RESTful APIs and microservices architecture.
Strong analytical and problem-solving skills, with a focus on delivering practical business solutions.

Soft Skills:

Excellent communication skills, both written and verbal.
Ability to work effectively in a fast-paced, collaborative environment.
Strong organizational skills and attention to detail.
Ability to manage multiple projects simultaneously and meet deadlines.

Academic Requirements:

Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. If you have a strong portfolio of complex applications/software/tools that you worked on, that would be terrific.

Experience Requirements:

3+ years of experience as a Machine Learning Engineer or in a similar role.

Monthly Salary:

BDT. 70,000 - 100,000 (depending on skills and experience).

Please email your resume to along with a proper subject line and a well-written cover letter that includes bullet-pointed career highlights. Clearly mention the number of years of your professional career and your expected monthly salary.

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