Description review

Tech Lead - Gen AI with 6+ Years

PradeepIT Consulting Services Pvt Ltd · India · back to the listing

HR standards

66/100

needs work

Title ↔ description

72/100

solid

Reads as

Machine Learning Engineer

100% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

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What the listing never says

  • 26 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Position: Tech Lead - Gen AI

Remote: Yes

Duration: 6 months extendable

Experience: 6+ Years

Working shift timing: India shift

Selection Process: Technical Round followed by Practice Round.

Job Description: Please find below

• Highly skilled Development Lead with expertise in Generative AI.

• Developing cutting-edge AI models and systems.

• Strong technical background and a passion for pushing the boundaries of AI technology.

• Responsibilities:

• Develop and implement advanced Generative AL models, with a specific focus on Text, Image generation and fine-tuning AI

• Collaborate with cross-functional teams to understand client requirements and translate them into scalable AI solutions.

• Research and explore emerging trends and techniques in the field of generative AI to stay at the forefront of innovation.

• Evaluate and fine-tune models to ensure high performance and accuracy.

• Collaborate with data scientists and engineers to integrate AI solutions into existing systems.

• Stay up-to-date with the latest advancements in the field of AI and contribute to the company's technical knowledge base.

Primary Technical Skills

• Must have Skills

Must have : Python

Proficiency in Python programming
End to End Understanding of back end work Flows
Good understanding of chatbots /Dialogue Flows
Good Understanding of NOSQL and Unstructured data
Ready to work on POC & Technical Evaluations

• Good to have Skills

• Good to have frameworks such as TensorFlow, Py-Torch, or Keras.

• Strong Good to have Basic knowledge of machine learning algorithms and their practical applications.

• Experience in feature engineering, and model evaluation.

• Familiarity and Hands-on Exp with one of cloud platforms such as AWS and Azure for scalable model deployment.

• Secondary Technical Skills:

• Basic Understanding of natural language processing (NLP) techniques and frameworks.

• Familiarity with computer vision and image processing techniques.

• Familiarity with distributed computing and parallel processing.

• Innovation and Technical Skills:

• Proven track record of developing innovative solutions and pushing the boundaries with the flavor of AI technology.

• Strong problem-solving skills and ability to think creatively.

• Basic understanding of machine learning principles and techniques.

• Ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.

• Strong analytical and critical thinking abilities.

Qualifications:

Degree in Computer Science, or a related field.

Some project experience in implementing Generative AI models and solutions in real-world applications.

Strong problem-solving and analytical skills.

Excellent communication and collaboration abilities.

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 8 points (from 74 before penalties). Reviewed 1 Oct 2026.