AI / ML Engineer

Experience : 4.00 + years

Salary : USD 2222-2592 / month (based on experience)

Expected Notice Period : 7 Days

Shift : (GMT+05 : 30) Asia / Kolkata (IST)

Opportunity Type : Remote

Placement Type : Full Time Contract for 6 Months(40 hrs a week / 160 hrs a month)

• Note : This is a requirement for one of Uplers' client - Hybrid AI)

What do you need for this opportunity

Must have skills required :

RecSys / decision optimization engines., Cloud (AWS / Azure / GCP), Data Pipelines (Celery, Databases (Cassandra, ELK), GPU / CUDA, Grafana, Kafka), ML Libraries (PyTorch, Monitoring (Prometheus, pandas, PyGAD), PySpark) + GPU / CUDA, Python (Django / FastAPI), Scikit-learn, TensorFlow, Kubernetes, PostgreSQL, Redis

Hybrid AI is Looking for :

About The Job

consumed optimally with our innovative SaaS B2B platform. Our mission is

to simplify decision-making for CIOs by providing tailored recommendations

that balances cost, power consumption, and compatibility with existing IT

environments. We take the complexity out of choosing the right

infrastructure, optimizing both cost and power consumption while delivering

high-performance AI and IT workloads.

brought to market by experienced software industry executives, addresses

the critical challenges CIOs face in navigating the rapidly evolving AI

landscape. By offering real-time, tailored recommendations, HybridAI

enables CIOs to make informed decisions quickly, reducing complexity and

driving immediate benefits. Join us at HybridAI and be part of a team that is

shaping the future of AI infrastructure with innovation, expertise, and a

commitment to excellence. You will build a system to balance cost,

performance, and power consumption.

Experience : 4-5 years

Type : 6 months contract

As an AI / ML Engineer at HybridAI, you'll be responsible for design, develop, and

scale AI-powered algorithms to optimize Kubernetes clusters, VMWare resource

allocation, GPU resource allocation, and cloud infrastructure - all with an AI-first

coding approach, embedding AI capabilities directly into product architecture from

day one.

Responsibilities

(cloud / on-prem, hardware type, cost / power trade-offs)

optimization strategies for large-scale infrastructure datasets.

systems for Kubernetes pods / VMs, including multi-GPU and fractional GPU

scenarios.

automated infrastructure decision-making, with real-time metric integration

(Prometheus, Grafana).

results, and document findings.

scikit-learn, and PySpark to feed infrastructure and performance metrics into ML

models.

using Celery task queues and workers in Python.

core SaaS application via REST or gRPC APIs.

MLOps tools.

practices

explainability

throughput and fast queries

and environments

transparency

What We're Looking For

production

central to system workflows.

infrastructure

processing and task scheduling

Why Join Us

How to apply for this opportunity

About Uplers :

Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.

(Note : There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Skills Required

Elk, Cassandra, Postgresql, Pyspark, Prometheus, Kafka, Grafana, Gpu, Tensorflow, Databases, Pytorch, Celery, Python, Monitoring, Aws, Redis, Cuda, Django, Pandas, Gcp, Cloud, FastAPI, Azure, Kubernetes