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Om Sai Global HR Services


Milling Machine Operator
Om Sai Global HR Services • New Delhi, Delhi • via Apna
7 days ago
₹20K–₹32K a month
Full–time
No Degree Mentioned
Apply on Apna
Job description
Job Description :-
We are looking for a skilled Machine Operator to set up, maintain and operate machinery. You’ll ensure the interminable and efficient running of production.
A great machine operator is reliable and able to work with attention to detail and safety standards. On-the-job training is a good way to discover how to do the job better, so you should have willingness to learn and improve. Being a team player is essential since all tasks will require close collaboration with co-workers.
The goal will be to ensure that production procedures will be carried on smoothly to maximize efficiency and profits.

Roles & Responsibilities:-
Set up machines (calibration, cleaning etc.) to start a production cycle.
Control and adjust machine settings (e.g. speed).
Feed raw material or parts to semi-automated machines.
Inspect parts with precision and measuring tools.
Test operation of machines periodically.
Fix issues that might occur during the shift.
Check output to spot any machine-related mistakes or flaws.
Keep records of approved and defective units or final products.

Requirements and skills:-
Proven at least 1-3 Years of experience as a machine operator.
Working knowledge of diverse high-speed machinery and measurement tools (caliper, micrometer etc.).
Understanding of production procedures.
Adherence to health and safety regulations (e.g. constant use of protective gear).
Ability to read blueprints, schematics and manuals.

More about this Milling Machine Operator job

Om Sai Global HR Services is aggressively hiring for the job profile of Milling Machine Operator at Delhi-NCR in Shankar Chowk Gurgaon locality. Kindly go through the FAQs below to get all answers related to the given job.

1. How much salary can I expect as a Milling Machine Operator in Om Sai Global HR Services in Delhi-NCR?

Ans. You can expect a minimum salary of 20,000 INR and can go up to 32,000 INR. The salary offered will depend on your skills, experience and performance in the interview.

2. What is the eligibility criteria to apply for Milling Machine Operator in Om Sai Global HR Services in Delhi-NCR?

Ans. The candidate should have completed 10th or Below 10th degree and people who have 1 to 31 years are eligible to apply for this job. You can apply for more jobs in Delhi-NCR to get hired quickly.

3. Is there any specific skill required for this job?

Ans. The candidate should have No English Required skills and sound communication skills for this job.

4. Who can apply for this job?

Ans. Only Male candidates can apply for this job.

5. Is it a work from home job?

Ans. No, it’s not a work from home job and can’t be done online. You can explore and apply for other work from home jobs in Delhi-NCR at apna.

6. Are there any charges or deposits required while applying for the role or while joining?

Ans. No work-related deposit needs to be made during your employment with the company.

7. How can I apply for this job?

Ans. Go to the apna app and apply for this job. Click on the apply button and call HR directly to schedule your interview.

8. What is the last date to apply?

Ans. The last date to apply for this job is 10-Oct-2024.

For more details, download apna app and find Full Time jobs in Delhi-NCR. Through apna, you can find jobs in 74 cities across India. Join NOW!
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Sprinklr


Director of Machine Learning - AI
Sprinklr • Gurugram, Haryana • via Instahyre
Full–time
Apply on Instahyre
Job description
Responsibilities:
• Develop and implement data science strategies to drive business growth.
• Collaborate with cross-functional teams to identify opportunities for data-driven insights and solutions.
• Lead the development of machine learning models using Python and other relevant tools.
• Conduct regular model maintenance and optimization to ensure accuracy and efficiency.
• Stay up-to-date with emerging trends and best practices in data science.
• Build cutting-edge capabilities utilizing machine learning and data science (e. g., large language models, computer vision models, voice models, etc. )
• Mentor, guide, coach, coordinate training opportunities, and support individual growth and technical skills across the engineering teams.
• Enable a continuous learning environment to keep abreast of industry trends. Partner with research organizations and explore innovation opportunities.
• Leverage industry best practices and tools to continually improve teams' ability to build, operate, and maintain products.
• Ensure that technical solutions are in line with established company strategy, and standards with respect to architecture, security, corporate governance, coding standards, monitoring, logging, unit test, and service enablement.
• As a director of machine learning, you will be responsible for overseeing the ML strategy, vision, and roadmap of your organization. You will also be leading and mentoring a team of ML professionals, and collaborating with other teams and departments.
• You are expected to grow a strong bench of ML/AI leaders to help Sprinklr further expand its ML/AI footprint in the company.

Requirements:
• Bachelor's or master's degree in computer science, mathematics, statistics, or related field.
• 8+ years of experience managing Machine Learning teams.
• 10+ years of experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed machine learning algorithms and systems.
• Proficient in Python, GEN AI, ML, Natural Language Processing (NLP), Deep Learning (DL), and Graph Analytics.
• Experience in directly working with cloud providers such as AWS, Azure, and GCP is a plus.
• Strong problem-solving skills and ability to work collaboratively in a team environment.
• Proficiency in operating machine learning solutions at scale, covering the end-to-end ML workflow.
• Familiarity with real-world ML systems (configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, and monitoring).
• Obsession for service observability, instrumentation, monitoring, and alerting.