Ariqt is hiring for AI/ML Engineer at Hyderabad

Posted on: 03/11/2025 | Location: Hyderabad | Experience: 1 – 2 Years



Job Summary

Ariqt is looking for an AI/ML Engineer to design, develop and deploy production-ready machine learning and deep learning models. The role expects hands-on work across model development, data pipelines, and collaboration with product and engineering teams to integrate AI into real-world applications. Interview rounds (for shortlisted candidates) are scheduled starting 8th November 2025 in Hyderabad. :contentReference[oaicite:0]{index=0}

Key Responsibilities

  • Design, build and optimize ML/DL models for production use.
  • Perform data preprocessing, feature engineering and exploratory data analysis (EDA).
  • Develop algorithms and solutions for NLP, computer vision and predictive analytics.
  • Evaluate and fine-tune models using appropriate metrics and benchmarks.
  • Build data ingestion, cleaning and transformation pipelines (ETL).
  • Create visualizations/dashboards and work with cross-functional teams for model integration.
  • Experiment with MLOps practices and emerging frameworks for scalable deployments.

(Job details from the Hirist posting.) :contentReference[oaicite:1]{index=1}

Required Qualifications

  • Bachelor’s or Master’s in Computer Science, Data Science, AI or related field.
  • Extensive experience in Python and ML libraries (NumPy, pandas, scikit-learn, TensorFlow/PyTorch).
  • Strong statistics, probability and data analysis background.
  • Good communicator and team player; experience with cloud platforms (AWS/Azure/GCP) preferred.
  • Preferred: experience in NLP, Computer Vision, Reinforcement Learning, and MLOps pipelines. :contentReference[oaicite:2]{index=2}

Salary structure (estimate & guidance)

The Hirist posting does not specify salary. Below are market-based ranges for Hyderabad / India (estimates aggregated from salary sites and market reports). Use these as a benchmark when negotiating:

  • Entry / Junior AI/ML Engineer (1–3 yrs): ₹5–12 LPA. :contentReference[oaicite:3]{index=3}
  • Mid-level ML Engineer (3–7 yrs): ₹10–22 LPA. :contentReference[oaicite:4]{index=4}
  • Senior / Lead ML Engineer (8+ yrs): ₹20–45+ LPA depending on product/company and equity/bonus. :contentReference[oaicite:5]{index=5}

Tip: Ask the recruiter about base vs. variable pay, signing bonus, stock/equity (if offered), and total cost-to-company (CTC) breakdown.

How to prepare for this role

Preparation split into technical, systems and soft-skills rounds:

Technical (Modeling & Coding)

  • Brush up on supervised learning, deep learning (CNNs, RNNs/Transformers), and evaluation metrics (precision/recall/F1, AUC, confusion matrix).
  • Practice implementing ML pipelines end-to-end in Python — data cleaning, feature engineering, model training, hyperparameter tuning and serialization.
  • Hands-on projects with TensorFlow or PyTorch (deploy a small model behind an API to demonstrate production thinking).
  • Familiarity with NLP (tokenization, BERT/transformer fine-tuning) and Computer Vision basics if applying for those tracks. :contentReference[oaicite:6]{index=6}

Systems, Deployment & MLOps

  • Practice building simple ETL/data pipelines and working knowledge of workflow tools (Airflow, Prefect) and containerization (Docker).
  • Understand cloud model deployment using AWS SageMaker, GCP AI Platform, or Azure ML — plus CI/CD basics for ML models.

Interview & Soft Skills

  • Prepare to explain past projects end-to-end (problem, dataset, features, model choice, metrics, deployment, lessons learned).
  • Expect system-design style questions for ML systems (scalability, inference latency, model monitoring and data drift).
  • Behavioural questions: collaboration with product/engineering, conflict resolution, stakeholder communication.

Practice Resources

  • Leetcode / InterviewBit for coding; Kaggle notebooks for hands-on modeling; Hugging Face tutorials for modern NLP.
  • Work through one production deployment (example: train model → containerize → expose REST endpoint) and include it in your portfolio.

Sample interview questions

  1. Explain bias–variance tradeoff and how you’d detect/mitigate it in a production model.
  2. Walk us through how you’d deploy an image-classification model with < 100ms inference latency requirement.
  3. How do you handle skewed class distributions? Describe techniques and trade-offs.
  4. Design a data pipeline for streaming sensor data that feeds an anomaly detection model.

About Ariqt (company snapshot)

Ariqt (Ariqt Global Technologies / Ariqt International) is an AI-led tech firm focused on AI agents, conversational assistants, mobile apps and other enterprise solutions. The company has recently launched a Global Innovation Hub (GIH) in Hyderabad and announced a hiring plan to bring in hundreds of engineers as part of its India expansion. Public company listings and local news reports note Ariqt’s Hyderabad innovation hub and hiring push. :contentReference[oaicite:7]{index=7}

Company legal & financial (public records)

Ariqt Global Technologies Private Limited appears in Indian registrar databases under incorporation date 22 May 2020; public filings and paid-up capital information are available on company-info portals (these entries are useful to cite during due-diligence). Note: detailed audited revenue/profit numbers were not published on the job listing — check company filings or ask the recruiter for recent financials. :contentReference[oaicite:8]{index=8}

Company culture & reviews (what job-seekers report)

  • Early-stage/fast-growth environment: hiring and innovation-focused (innovation hub announcements indicate rapid hiring/scale-up).
  • International clientele / product orientation — many roles mention working with global clients and cross-functional teams.
  • Typical trade-offs: fast-paced growth can mean shifting priorities and hands-on responsibilities beyond strict job descriptions. :contentReference[oaicite:9]{index=9}

Tip: Try to talk with current or ex-employees on LinkedIn for role-specific insights before joining — ask about onboarding, mentorship and review cycles.

Profits & financial details (what we know)

Public corporate-information portals list Ariqt’s Indian registration and basic capital/AGM dates; however, comprehensive audited revenue/profit details were not available in the job listing. For accurate financials request audited statements directly from the company or search MCA / Registrar filings. :contentReference[oaicite:13]{index=13}

Pros & Cons (for a job-seeker)

Pros

  • Opportunity to work on AI products and production ML systems.
  • Fast-growing company with active hiring — good for career acceleration.
  • Hyderabad innovation hub — likely proximity to strong local engineering talent & ecosystem. :contentReference[oaicite:14]{index=14}

Cons

  • Smaller/private companies may have less publicly available financial transparency.
  • Rapid growth phases can bring organizational changes and occasional role ambiguity.
  • Salary benchmark varies widely — negotiate total CTC and benefits clearly. :contentReference[oaicite:15]{index=15}

How to apply

  1. Click the Apply button at the top which links to the Hirist job posting. (Use the Hirist application to submit resume & cover letter.)
  2. In your cover letter, highlight one or two production ML projects, the business outcome, and your role in deployment/monitoring.
  3. If shortlisted, expect rounds scheduled from 8th November 2025 for Hyderabad (per the listing). :contentReference[oaicite:16]{index=16}



Sources: Hirist job listing (job description & interview date), Ariqt company website, press coverage on Ariqt Hyderabad innovation hub, and public company registration portals. Check source links when sharing on your blog. :contentReference[oaicite:17]{index=17}

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