Technical Content Writer

Job Description

Key Responsibilities

• Develop persona-driven, high-impact content across various formats, including:
  

• Technical blogs, white papers, solution briefs, and articles
  

• Use-case explainers, tutorials, case studies, and how-to guides
  

• SEO-optimized website and landing page content
  

• Marketing assets such as email campaigns, ad copy, and sales funnel content
  

• Internal and external training material
  

• Video scripts (short-form and long-form), newsletters, and product overviews
  

• Write on advanced technology topics such as:
  

• Generative AI, Agentic AI, RAG pipelines, LLMs, GPTs
  

• Data Engineering tools – Kafka, Apache Spark,Snowflake
  

• Cloud platforms, MLOps pipelines, and AI agent development
  

• Collaborate with SMEs, engineers, and design teams to create accurate, impactful, and human-centered content.
  

• Ensure tone, clarity, and consistency across all deliverables while meeting SEO and readability standards.
  

• Edit and refine content using tools for SEO, originality, and AI detection.
  

• Support cross-functional teams, including product marketing, sales enablement, and training.
  

Requirements

Required Skills & Qualifications

• 3–4 years of experience as a Technical Content Writer, preferably in IT consulting, SaaS, or enterprise training domains.
  

• Bachelor's degree in Computer Science, Information Technology, or a related field.
  

• Strong understanding of AI/ML concepts, data platforms, and cloud technologies.
  

• Excellent writing, research, and editorial skills with the ability to simplify complex ideas.
  

• Proficiency in SEO best practices, keyword research, and the use of AI detection/piracy tools.
  

• Familiarity with LLM chatbots, generative AI platforms, and prompt engineering is a strong plus.
  

• Self-motivated, detail-oriented, and capable of managing multiple content pieces simultaneously.
  

Benefits

• Work on the front lines of AI, cloud, and data innovation
  

• Collaborate with global thought leaders and enterprise clients
  

• Be part of a growing content team with creative freedom and real impact
  

• Competitive compensation and a learning-focused work environment
  

Requirements
Educational Background: Bachelor's and Master’s degrees in Data Science, Computer Science, Statistics, or a related field. Technical Skills: Proficient in Python and familiar with key data science libraries (Pandas, Scikit-Learn, TensorFlow, or PyTorch). Strong understanding of all complex machine learning algorithms not limited to decision trees, random forests, and gradient boosting machines. Competence in data preprocessing, cleaning, and analysis. Familiarity with data cleaning, transformation, and preprocessing techniques. Experience with SQL and possibly some NoSQL databases for data querying and manipulation. Basic knowledge of data visualization tools like Matplotlib and Seaborn. Strong skills in SQL for data extraction, and the ability to work with complex database systems. Advanced knowledge of analytical tools and software such as Excel, Tableau, or more specialized software depending on the industry (e.g., SAS, SPSS). Experience with data visualization and the ability to create interactive dashboards. Vast knowledge of NLP, Deep Learning, Machine Learning , Knowledge of genAI with implementation knowledge (LLM, fine tuning RAG implementation) and many more. Familiarity with cloud services (AWS, Azure, Google Cloud) for data processing and storage.. Professional Experience: 2-3 years of experience in a data science or related role. Proven track record of developing and deploying machine learning models to solve business problems. Experience in projects that involve complex data structures and large-scale datasets. Exposure to model validation and implementation in a production environment. Demonstrated experience in analyzing large datasets and delivering actionable insights. Proven track record of effectively communicating findings to help inform business decisions. Experience in performing statistical analysis, forecasting, and establishing data structures that optimize analytical capabilities. Soft Skills: Strong problem-solving skills with a capability to work through complex issues using a logical and analytical approach. Good communication skills to effectively articulate insights and technical details to non-technical stakeholders. Ability to work collaboratively in team settings and manage project timelines effectively. Strong attention to detail with the capability to work on multiple projects simultaneously. Effective communication skills, capable of presenting complex information in an understandable and compelling manner. Collaboration skills to work effectively with both technical teams and business units.