Support Co ordinator (Help Desk)

Senior Machine Learning Engineer

About the Role

We are looking for a Senior Machine Learning Engineer who can take business problems, design appropriate machine learning solutions, and make them work reliably in production environments.

This role is ideal for someone who not only understands machine learning models, but also knows when and how ML should be applied, what trade-offs to make, and how to take ownership from problem understanding to production deployment.

Beyond technical skills, we need someone who can lead a team of ML Engineers, design end-to-end ML solutions, and clearly communicate decisions and outcomes to both engineering teams and business stakeholders. If you enjoy solving real problems, making pragmatic decisions, and owning outcomes from idea to deployment, this role is for you.

What You’ll Be Doing

Building and Deploying ML Models

• Design, build, evaluate, deploy, and monitor machine learning models for real production use cases.
• Take ownership of how a problem is approached, including deciding whether ML is the right solution and what type of ML approach fits the problem.
• Ensure scalability, reliability, and efficiency of ML pipelines across cloud and on-prem environments.
• Work with data engineers to design and validate data pipelines that feed ML systems.
• Optimize solutions for accuracy, performance, cost, and maintainability, not just model metrics.

Leading and Architecting ML Solutions

• Lead a team of ML Engineers, providing technical direction, mentorship, and review of ML approaches.
• Architect ML solutions that integrate seamlessly with business applications and existing systems.
• Ensure models and solutions are explainable, auditable, and aligned with business goals.
• Drive best practices in MLOps, including CI/CD, model monitoring, retraining strategies, and operational readiness.
• Set clear standards for how ML problems are framed, solved, and delivered within the team.

Collaborating and Communicating

• Work closely with business stakeholders to understand problem statements, constraints, and success criteria.
• Translate business problems into clear ML objectives, inputs, and expected outputs.
• Collaborate with software engineers, data engineers, platform engineers, and product managers to integrate ML solutions into production systems.
• Present ML decisions, trade-offs, and outcomes to non-technical stakeholders in a simple and understandable way.

What We’re Looking For

Machine Learning Expertise

• Strong understanding of supervised and unsupervised learning, deep learning, NLP techniques, and large language models (LLMs).
• Experience choosing appropriate modeling approaches based on the problem, available data, and business constraints.
• Experience training, fine-tuning, and deploying ML and LLM models for real-world use cases.
• Proficiency in common ML frameworks such as TensorFlow, PyTorch, Scikit-learn, etc.

Production and Cloud Deployment

• Hands-on experience deploying and running ML systems in production environments on AWS, GCP, or Azure.
• Good understanding of MLOps practices, including CI/CD for ML models, monitoring, and retraining workflows.
• Experience with Docker, Kubernetes, or serverless architectures is a plus.
• Ability to think beyond deployment and consider operational reliability and long-term maintenance.

Data Handling

• Strong programming skills in Python.
• Proficiency in SQL and working with large-scale datasets.
• Ability to reason about data quality, data limitations, and how they impact ML outcomes.
• Familiarity with distributed computing frameworks like Spark or Dask is a plus.

Leadership and Communication

• Ability to lead and mentor ML Engineers and work effectively across teams.
• Strong communication skills to explain ML concepts, decisions, and limitations to business teams.
• Comfortable taking ownership and making decisions in ambiguous problem spaces.
• Passion for staying updated with advancements in ML and AI, with a practical mindset toward adoption.

Experience Needed

• 6+ years of experience in machine learning engineering or related roles.
• Proven experience designing, selecting, and deploying ML solutions used in production.
• Experience managing ML systems after deployment, including monitoring and iteration.
• Proven track record of working in cross-functional teams and leading ML initiatives.

Manage end to end travel plans pan India efficiently and cost-effectively – airlines, trains, transport, and hotels.  Negotiate on best rates through vendors every time there is a travel occurrence.  Communicate with the person travelling regularly to keep them updated on logistics.  Manage emergency changes/cancellations in a professional and calm manner.  Handle visa applications and formalities promptly.  Handle all incoming travel requests and the processes that follow after.

Proven experience in sales and business development, preferably within the

education sector, specifically in selling admission management solutions to CBSE,

ICSE, IGCSE, IB, and boarding schools.

● Strong understanding of the admission processes and challenges faced by

educational institutions.

● Excellent communication and presentation skills, with the ability to effectively

engage with school stakeholders at all levels.

● The proactive and results-driven mindset with a track record of meeting or

exceeding sales targets.

● Ability to build and nurture long-term relationships with customers.

● Strong negotiation and closing skills, with attention to detail in contract and

agreement management.

● Exceptional organizational and time management skills, with the ability to prioritize

tasks effectively.

● Willingness to travel within the assigned territory as required.

Company : Barcadly Services (www.barcadlyservices.com)

Job Title: Business Development Executive (BDE)

Overview:

As a Business Development Executive, your primary responsibility is to identify new business opportunities and build relationships with potential clients. You will be responsible for developing and implementing strategies that will drive revenue growth and increase market share.

Key Responsibilities:

• Conduct market research to identify new business opportunities and potential clients

• Develop and maintain a pipeline of potential clients

• Build and maintain relationships with key decision-makers within the target market

• Develop and implement strategies to increase sales and revenue growth

• Negotiate and close business deals with clients

• Collaborate with other departments within the organization to ensure the delivery of high-quality products or services

• Keep up to date with industry trends, competitor activities, and regulatory changes that may impact the business

• Monitor and report on sales performance and adjust strategies accordingly

• Attend industry events and conferences to build relationships and promote the organization

Requirements:

• Bachelor's degree in Business, Marketing, or a related field

• Proven track record of successful business development or sales experience

• Excellent communication, negotiation, and interpersonal skills

• Ability to work independently and in a team environment

• Strong analytical and problem-solving skills

• Ability to manage multiple projects and priorities

Position: Senior Analyst QA (Automation Testing)

Experience: 4-6 years

Years Location: Bengaluru

We are a multi-award-winning creative engineering company offering design and technology solutions onmobile, web and cloud platforms. We are looking for an enthusiastic and self-driven Test Engineer to join ourteam.

Roles and Responsibilities:

• Responsible fortesting Web Application.

• Responsible for Automation testing: Design, develop and execute automation scripts using open-source tools like Appium, Selenium and QMetry.

• Responsible for writing clear, concise, and comprehensive test plans and test cases.

• Handle ClientInteractions

Desired Profile:

• Extensive experience in Automation Testing of web application

• Experience in Manual Testing

• Hands-on testing experience on Selenium, Appium, QMetry.

• Strong knowledge ofsoftware QA methodologies, tools, and processes • Experience with performance and/orsecurity testing is a plus.

• Excellent Communication Skills & Client Interactions.

Good to Have:

• Experience in manual testing

• KPI driven

• Should be a team player

• Independently evaluates issues and proposes solutions

• Raises issues/concerns on time

• Good if he/she has experience testing AI/ML model

Qualifications:

MCA, BE/B.Tech - All Regular - 65% Above 

Mactores is a trusted leader among businesses in providing modern data platform solutions. Since 2008, Mactores have been enabling businesses to accelerate their value through automation by providing End-to-End Data Solutions that are automated, agile, and secure. We collaborate with customers to strategize, navigate, and accelerate an ideal path forward with a digital transformation via assessments, migration, or modernization.

We are looking for a DataOps Engineer with expertise while operating a data lake. Amazon S3, Amazon EMR, and Apache Airflow for workflow management are used to build the data lake.

You have experience of building and running data lake platforms on AWS. You have exposure to operating PySpark-based ETL Jobs in Apache Airflow and Amazon EMR. Expertise in monitoring services like Amazon CloudWatch.

If you love solving problems using yo, professional services background, usual and fun office environment that actively steers clear of rigid "corporate" culture, focuses on productivity and creativity, and allows you to be part of a world-class team while still being yourself.

What you will do?

• Operate the current data lake deployed on AWS with Amazon S3, Amazon EMR, and Apache Airflow
• Debug and fix production issues in PySpark.
• Determine the RCA (Root cause analysis) for production issues.
• Collaborate with product teams for L3/L4 production issues in PySpark.
• Contribute to enhancing the ETL efficiency
• Build CloudWatch dashboards for optimizing the operational efficiencies
• Handle escalation tickets from L1 Monitoring engineers
• Assign the tickets to L1 engineers based on their expertise

What are we looking for?

• AWS data Ops engineer.
• Overall 5+ years of exp in the software industry Exp in developing architecture data applications using python or scala, Airflow, and Kafka on AWS Data platform Experience and expertise.
• Must have set up or led the project to enable Data Ops on AWS or any other cloud data platform.
• Strong data engineering experience on Cloud platform, preferably AWS.
• Experience with data pipelines designed for reuse and use parameterization.
• Experience of pipelines was designed to solve common ETL problems.
• Understanding or experience on various AWS services can be codified for enabling DataOps like Amazon EMR, Apache Airflow.
• Experience in building data pipelines using CI/CD infrastructure.
• Understanding of Infrastructure as code for DataOps ennoblement.
• Ability to work with ambiguity and create quick PoCs.

You will be preferred if

• Expertise in Amazon EMR, Apache Airflow, Terraform, CloudWatch
• Exposure to MLOps using Amazon Sagemaker is a plus.
• AWS Solutions Architect Professional or Associate Level Certificate
• AWS DevOps Professional Certificate

Life at Mactores

We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.

1. Be one step ahead

2. Deliver the best

3. Be bold

4. Pay attention to the detail

5. Enjoy the challenge

6. Be curious and take action

7. Take leadership

8. Own it

9. Deliver value

10. Be collaborative

We would like you to read more details about the work culture on https://mactores.com/careers 

The Path to Joining the Mactores Team

At Mactores, our recruitment process is structured around three distinct stages:

Pre-Employment Assessment: 

You will be invited to participate in a series of pre-employment evaluations to assess your technical proficiency and suitability for the role.

Managerial Interview: The hiring manager will engage with you in multiple discussions, lasting anywhere from 30 minutes to an hour, to assess your technical skills, hands-on experience, leadership potential, and communication abilities.

HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team.

At Mactores, we are committed to providing equal opportunities in all of our employment practices, and we do not discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This policy extends to all aspects of the employment relationship, including recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs. All employment decisions will be made in compliance with these principles.