Greenko's 2023
Off-Campus Recruitment Drive: Hiring Fresh Graduate Engineer Trainees for Wind
Power Generation in Hyderabad, India
Looking
for a career in the sustainable energy industry? Join Greenko's 2023 Off-Campus
Recruitment Drive for Graduate Engineer Trainees in Wind Power Generation at
their Hyderabad location. As a trainee, you will have the opportunity to work
with emerging technologies, develop AI-based systems, and collaborate with a
team of engineers to improve the overall efficiency and sustainability of power
generation processes. Apply now and be a catalyst for transformation in the
energy sector.
Admin
Office , Hyderabad, Telangana, India
Department
GAM - Wind
Job posted on
May 8, 2023
Employee Type
Trainee
Experience range (Years)
0 - 1 year
Job Description: Graduate Engineer Trainee's (Premier
Universities)
Job Summary:
The candidates are expected to be well conversant
with the aspects related to the Wind power generation, incl. good understanding
of Electrical & Mechanical generating Plant & Machinery and
systems.
should have good knowledge of Automation, Digitisation,
SCADA and then AI & ML and Data Analytics, preferably that relevant to
Wind-electric power generation.
•are expected to be ‘Future Ready’ and ‘Catalysts for
Transformation’ from Conventional to Smart Working. Should have good appetite
for Innovative / Out-of-box thinking, experimentation, research and towards
emerging state-of-the -art technologies.
•Should be able to grasp, adopt, develop new technologies
and solutions to improve the overall efficiency and sustainability of power
generation processes. Should be able to conduct feasibility studies and
cost-benefit analysis of the proposed implementations and develop and maintain
related technical documentation and records.
•Should be able to foster culture of creativity and
collaborate with the Engineers, Operators and Maintenance staff for
implementing newer technologies and solutions at the plants.
Typical work assignments:
•To Develop AI based systems for real time monitoring of
the plants that can analyse data and infer the trends to detect and diagnose
any deteriorations and predict faults and probable equipment failures so as to
prevent them well in advance and also provide insights into the overall health
of the plant.
•To extend the support & work closely with teams who
are dealing Technical services, Performance Optimisation and Loss Analysis
& Condition based monitoring.
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